AIIM by ELEOS
Where Artificial Intelligence meets Medicine
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AI-Based Selection of Individuals for Supplemental MRI in Population-Based Breast Cancer Screening: The Randomized ScreenTrustMRI Trial
Oncology•
Large Language Models and the Degradation of the Medical Record
Medical Informatics•
A Novel Artificial Intelligence–powered Tool for Precise Risk Stratification of Prostate Cancer Progression in Patients with Clinical Intermediate Risk
Urology•
AI-enhanced analysis of naturalistic social interactions characterizes interaffective impairments in schizophrenia
Psychiatry•
Accurate Machine Learning Prediction in Psychiatry Needs the Right Kind of Information
Psychiatry•
Cost-Effectiveness of AI for Risk-Stratified Breast Cancer Screening
Oncology•
Federated Learning for Decentralized Artificial Intelligence in Melanoma Diagnostics
Dermatology•
Current State of Dermatology Mobile Applications With Artificial Intelligence Features
Dermatology•
Harnessing Artificial Intelligence for the Diagnosis and Treatment of Neurological Emergencies: A Comprehensive Review of Recent Advances and Future Directions
Neurology•
Natural and Artificial Intelligence: A brief introduction to the interplay between AI and neuroscience research
Neurology•
Artificial intelligence in ophthalmology: The path to the real-world clinic
Ophthalmology•
Deconstructing Cognitive Impairment in Psychosis With a Machine Learning Approach
Psychiatry•
Using machine learning modeling to identify childhood abuse victims on the basis of personality inventory responses
Psychiatry•
Multimodal Machine Learning Workflows for Prediction of Psychosis in Patients With Clinical High-Risk Syndromes and Recent-Onset Depression
Psychiatry•
Development and Clinical Evaluation of an Artificial Intelligence Support Tool for Improving Telemedicine Photo Quality
Dermatology•
Advances in Melanoma-Nevus Classification Using Artificially Generated Image Data Sets
Dermatology•
Current status and practical considerations of artificial intelligence use in screening and diagnosing retinal diseases: Vision Academy retinal expert consensus
Ophthalmology•
Transforming orthopedics: A glimpse into the future with artificial intelligence
Orthopedics•
Artificial Intelligence for Hip Fracture Detection and Outcome Prediction: A Systematic Review and Meta-analysis
Orthopedics•
Integration of a deep learning basal cell carcinoma detection and tumor mapping algorithm into the Mohs micrographic surgery workflow and effects on clinical staffing: A simulated, retrospective study
Dermatology•
Usage of digital information and communications technologies in patients with hidradenitis suppurativa
Dermatology•
The utility of artificial intelligence platforms for patient-generated questions in Mohs micrographic surgery: a multi-national, blinded expert panel evaluation
Dermatology•
Use of Artificial Intelligence Chatbots for Cancer Treatment Information
Oncology•
Precise reconstruction of the TME using bulk RNA-seq and a machine learning algorithm trained on artificial transcriptomes
Oncology•
Association of Machine Learning–Based Assessment of Tumor-Infiltrating Lymphocytes on Standard Histologic Images With Outcomes of Immunotherapy in Patients With NSCLC
Oncology•
Shareable artificial intelligence to extract cancer outcomes from electronic health records for precision oncology research
Oncology•
Machine learning identifies experimental brain metastasis subtypes based on their influence on neural circuits
Oncology•
Improving treatment completion for young adults with substance use disorder: Machine learning-based prediction algorithms
Psychiatry•
Artificial intelligence in ophthalmology
Ophthalmology•
Use of an Artificial Intelligence Device for Evaluating Blood Loss in Complex Major Orthopaedic Surgery Procedures
Orthopedics•
Novel Technique for the Identification of Hip Implants Using Artificial Intelligence
Orthopedics•
Evaluating the appropriateness of skin cancer prevention recommendations obtained from an online chat-based artificial intelligence model
Dermatology•
Evaluation of the Accuracy of Artificial Intelligence (AI) Models in Dermatological Diagnosis and Comparison With Dermatology Specialists
Dermatology•
Testing the ability of artificial intelligence chatbots and dermatologic diagnosis mobile applications to diagnose melanoma and seborrheic keratosis
Dermatology•
Advancing presurgical non-invasive molecular subgroup prediction in medulloblastoma using artificial intelligence and MRI signatures
Oncology•
Predicting Drug Response and Synergy Using a Deep Learning Model of Human Cancer Cells
Oncology•
A vision–language foundation model for precision oncology
Oncology•
Racial and Ethnic Disparities in Predictive Accuracy of Machine Learning Algorithms Developed Using a National Database for 30-Day Complications Following Total Joint Arthroplasty
Orthopedics•
Utilization of Machine Learning Models to More Accurately Predict Case Duration in Primary Total Joint Arthroplasty
Orthopedics•
EEG based depression detection by machine learning: Does inner or overt speech condition provide better biomarkers when using emotion words as experimental cues?
Psychiatry•
Digital Pathology–based Artificial Intelligence Biomarker Validation in Metastatic Prostate Cancer
Urology•
A Systematic Review of the Diagnostic Accuracy of Deep Learning Models for the Automatic Detection, Localization, and Characterization of Clinically Significant Prostate Cancer on Magnetic Resonance Imaging
Urology•
Spatially resolved transcriptomics and graph-based deep learning improve accuracy of routine CNS tumor diagnostics
Oncology•
A multi-modal deep learning model for prediction of Ki-67 for meningiomas using pretreatment MR images
Oncology•
Decoding pan-cancer treatment outcomes using multimodal real-world data and explainable artificial intelligence
Oncology•
Artificial intelligence links CT images to pathologic features and survival outcomes of renal masses
Oncology•
Generative artificial intelligence in neurology: Opportunities and risks
Neurology•
Revolutionizing Neurology: The Role of Artificial Intelligence in Advancing Diagnosis and Treatment
Neurology•
Artificial intelligence for clinical decision support in neurology
Neurology•
Current roles of artificial intelligence in ophthalmology
Ophthalmology•
A Deep Learning Tool for Minimum Joint Space Width Calculation on Antero-posterior Knee Radiographs
Orthopedics•
High specificity of an AI-powered framework in cross-checking male professional football anterior cruciate ligament tear reports in public databases
Orthopedics•
A machine learning prediction model for total shoulder arthroplasty procedure duration: an evaluation of surgeon, patient, and shoulder-specific factors
Orthopedics•
Automatic three-dimensional analysis of posterosuperior full-thickness rotator cuff tear size on MRI
Orthopedics•
Applications of Machine Learning in Prognostication of Mild Traumatic Brain Injury
PM&R•
Identifying subgroups of urge suppression in Obsessive-Compulsive Disorder using machine learning
Psychiatry•
Ethics Principles for Artificial Intelligence-Based Telemedicine for Public Health
Public Health•
Artificial intelligence, ChatGPT, and other large language models for social determinants of health: Current state and future directions
Public Health•
Tomorrow’s patient management: LLMs empowered by external tools
Urology•
ChatGPT can help guide and empower patients after prostate cancer diagnosis
Urology•
Nationwide real-world implementation of AI for cancer detection in population-based mammography screening
Oncology•
Multi-task AI models in dermatology: Overcoming critical clinical translation challenges for enhanced skin lesion diagnosis
Dermatology•
Evaluation of an artificial intelligence-based decision support for the detection of cutaneous melanoma in primary care: a prospective real-life clinical trial
Dermatology•
Translational gaps and opportunities for medical wearables in digital health
PM&R•
Challenges of Developing a Natural Language Processing Method With Electronic Health Records to Identify Persons With Chronic Mobility Disability
PM&R•
Prevention and management of degenerative lumbar spine disorders through artificial intelligence-based decision support systems: a systematic review
Orthopedics•
Achieving high accuracy in meniscus tear detection using advanced deep learning models with a relatively small data set
Orthopedics•
Artificial Intelligence-Based Surgery Support Model Using Intraoperative Radiographs for Assessing the Acetabular Component Angle
Orthopedics•
Development of a Deep Learning Model for Automating Implant Position in Total Hip Arthroplasty
Orthopedics•
Predicting Early Hospital Discharge Following Revision Total Hip Arthroplasty: An Analysis of a Large National Database Using Machine Learning
Orthopedics•
An artificial intelligence application to predict prolonged dependence on mechanical ventilation among patients with critical orthopaedic trauma: an establishment and validation study
Orthopedics•
Machine learning models predicting risk of revision or secondary knee injury after anterior cruciate ligament reconstruction demonstrate variable discriminatory and accuracy performance: a systematic review
Orthopedics•
Ethical implication of artificial intelligence in skin cancer diagnostics: use-case analyses
Dermatology•
Incidence and patterns of newly developed pigmented lesions in adults at high risk for melanoma
Dermatology•
A deep multiple instance learning framework improves microsatellite instability detection from tumor next generation sequencing
Oncology•
Deep learning predicts therapy-relevant genetics in acute myeloid leukemia from Pappenheim-stained bone marrow smears
Oncology•
Artificial intelligence assisted real-time recognition of intra-abdominal metastasis during laparoscopic gastric cancer surgery
Oncology•
Deep Learning Model for Predicting Immunotherapy Response in Advanced Non−Small Cell Lung Cancer
Oncology•
Evaluation of the Ability of Machine Learning-Models to Assess Postural Orientation Errors During a Single-Leg Squat
Orthopedics•
Quantifying knee-adjacent subcutaneous fat in the entire OAI baseline dataset – Associations with cartilage MRI T2, thickness and pain, independent of BMI
Orthopedics•
Data-Driven Approach to Development of a Risk Score for Periprosthetic Joint Infections in Total Joint Arthroplasty Using Electronic Health Records
Orthopedics•
Diagnostic Accuracy and Interobserver Reliability of Rotator Cuff Tear Detection with Ultrasonography are Improved with Attentional Deep Learning
Orthopedics•
Developing a Computer Vision Model to Automate Quantitative Measurement of Hip-Knee-Ankle Angle in Total Hip and Knee Arthroplasty Patients
Orthopedics•
Predictive analysis of economic and clinical outcomes in total knee arthroplasty: Identifying high-risk patients for increased costs and length of stay
Orthopedics•
Characterizing Osteophyte Formation in Knee Osteoarthritis: Application of Machine Learning Quantification of a Computerized Tomography Cohort: Implications for Treatment
Orthopedics•
AKIRA: Deep learning tool for image standardization, implant detection and arthritis grading to establish a radiographic registry in patients with anterior cruciate ligament injuries
Orthopedics•
Effect of an Artificial Intelligence–Based Self-Management App on Musculoskeletal Health in Patients With Neck and/or Low Back Pain Referred to Specialist Care: A Randomized Clinical Trial
PM&R•
Mining Clinical Notes for Physical Rehabilitation Exercise Information: Natural Language Processing Algorithm Development and Validation Study
PM&R•
Optimizing uni-compartmental knee arthroplasty: the impact of preoperative planning and arithmetic hip-knee-ankle angle
Orthopedics•
Predictive Tool Use and Willingness for Surgery in Patients With Knee Osteoarthritis: A Randomized Clinical Trial
Orthopedics•
Predicting periprosthetic joint infection in primary total knee arthroplasty: a machine learning model integrating preoperative and perioperative risk factors
Orthopedics•
Artificial intelligence for breast cancer screening in mammography (AI-STREAM): preliminary analysis of a prospective multicenter cohort study
Oncology•
Generative artificial intelligence in ophthalmology
Ophthalmology•
External validation of an artificial intelligence multi-label deep learning model capable of ankle fracture classification
Orthopedics•
Deep learning to combat knee osteoarthritis and severity assessment by using CNN-based classification
Orthopedics•
Deep learning-based automated measurement of hip key angles and auxiliary diagnosis of developmental dysplasia of the hip
Orthopedics•
Diagnostic accuracy of deep learning in prediction of osteoporosis: a systematic review and meta-analysis
Orthopedics•
Artificial Intelligence in Commercial Industry: Serving the End-to-End Patient Experience Across the Digital Ecosystem
Orthopedics•
Machine learning-based radiomics using MRI to differentiate early-stage Duchenne and Becker muscular dystrophy in children
Orthopedics•
Spinal navigation with AI-driven 3D-reconstruction of fluoroscopy images: an ex-vivo feasibility study
Orthopedics•
What does best evidence tell us about robotic gait rehabilitation in stroke patients: A systematic review and meta-analysis
PM&R•
Validation of anorexia nervosa and bulimia nervosa diagnosis coding in Danish hospitals assisted by a natural language processing model
Psychiatry•
High-resolution spatially resolved proteomics of complex tissues based on microfluidics and transfer learning
Oncology•
Particle uptake in cancer cells can predict malignancy and drug resistance using machine learning
Oncology•
Explainable artificial intelligence of DNA methylation-based brain tumor diagnostics
Oncology•
Comprehensive Review on the Use of Artificial Intelligence in Ophthalmology and Future Research Directions
Ophthalmology•
Impact of artificial intelligence in managing musculoskeletal pathologies in physiatry: a qualitative observational study evaluating the potential use of ChatGPT versus Copilot for patient information and clinical advice on low back pain
PM&R•
The Journal of Arthroplasty
Orthopedics•
Uncertainty-Aware Deep Learning Characterization of Knee Radiographs for Large-Scale Registry Creation
Orthopedics•
Digital twin systems for musculoskeletal applications: A current concepts review
Orthopedics•
Racial and Ethnic Disparities in Predictive Accuracy of Machine Learning Algorithms Developed Using a National Database for 30-Day Complications Following Total Joint Arthroplasty
Orthopedics•
Development and accuracy of an artificial intelligence model for predicting the progression of hip osteoarthritis using plain radiographs and clinical data: a retrospective study
Orthopedics•
Artificial intelligence improves the accuracy of residents in the diagnosis of hip fractures: a multicenter study
Orthopedics•
Automatic segmentation of human knee anatomy by a convolutional neural network applying a 3D MRI protocol
Orthopedics•
Automatic segmentation of human knee anatomy by a convolutional neural network applying a 3D MRI protocol
Orthopedics•
Is AI 3D-printed PSI an accurate option for patients with developmental dysplasia of the hip undergoing THA?
Orthopedics•
Exploring the Impact of Artificial Intelligence on Global Health and Enhancing Healthcare in Developing Nations
Public Health•
Exploring the Impact of Artificial Intelligence on Global Health and Enhancing Healthcare in Developing Nations
Public Health•
Integrating machine learning and artificial intelligence in life-course epidemiology: pathways to innovative public health solutions
Public Health•
ReconGPT: A novel artificial intelligence tool and its potential use in post-Mohs reconstructive decision-making
Dermatology•
zero-Shot Extraction of Seizure Outcomes from Clinical Notes Using Generative Pretrained Transformers
Dermatology•
Application of Artificial Intelligence in Ophthalmology: An Updated Comprehensive Review
Ophthalmology•
Current roles of artificial intelligence in ophthalmology
Ophthalmology•
Development of an artificial intelligence model for predicting implant size in total knee arthroplasty using simple X-ray images
Orthopedics•
Integrated analysis of bioinformatics, mendelian randomization, and experimental validation reveals novel diagnostic and therapeutic targets for osteoarthritis: progesterone as a potential therapeutic agent
Orthopedics•
Artificial intelligence: the unstoppable revolution in ophthalmology
Ophthalmology•
Applications of Artificial Intelligence in Ophthalmology: Glaucoma, Cornea, and Oculoplastics
Ophthalmology•
EEG microstate analysis and machine learning classification in patients with obsessive-compulsive disorder
Neurology•
Feasibility of Artificial Intelligence-Assisted Quantitative Muscle Ultrasound in Carpal Tunnel Syndrome
Neurology•
Advanced feature fusion of radiomics and deep learning for accurate detection of wrist fractures on X-ray images
Radiology•
A Machine Learning Method to Determine Candidates for Total and Unicompartmental Knee Arthroplasty Based on a Voting Mechanism
Orthopedics•
Capturing the Electrical Activity of all Cortical Neurons: Are Solutions Within Reach?
Neurotechnology•
Exploring healthcare professionals' perceptions of artificial intelligence: Piloting the Shinners Artificial Intelligence Perception tool
Healthcare Technology•
Genetic and Clinical Correlates of AI-Based Brain Aging Patterns in Cognitively Unimpaired Individuals
Neurology•
Classification of non-TCGA cancer samples to TCGA molecular subtypes using compact feature sets
Oncology•
Development of a Machine Learning Model for Determining Alignment in Knees Following Total Knee Arthroplasty
Orthopedics•
Machine-Learning Algorithms to Automate Morphological and Functional Assessments in 2D Echocardiography
Cardiology/Cardiovascular Surgery•
Artificial intelligence in ophthalmology
Ophthalmology•
Generative artificial intelligence in ophthalmology: current innovations, future applications and challenges
Ophthalmology•
Artificial intelligence: the unstoppable revolution in ophthalmology
Ophthalmology•
Estimated Average Treatment Effect of Psychiatric Hospitalization in Patients With Suicidal Behaviors – A Precision Treatment Analysis
Psychiatry•
AI image generation technology in ophthalmology: Use, misuse and future applications
Ophthalmology•
Artificial intelligence: the unstoppable revolution in ophthalmology
Ophthalmology•
Reporting Guidelines for Artificial Intelligence Use in Orthopaedic Surgery Research
Orthopedics•
Artificial Intelligence Applications in the Management of Musculoskeletal Disorders of the Shoulder: A Systematic Review
Orthopedics•
A Machine Learning Trauma Triage Model for Critical Care Transport
Emergency Medicine•
Clinical implementation of AI-assisted detection of breast cancer metastases in sentinel lymph nodes (CONFIDENT-B trial)
Oncology•
Wearable peripheral nerve stimulator reduces essential tremor symptoms through targeted brain modulation
Neurotechnology•
Testing behaviour change with an artificial intelligence chatbot in a randomized controlled study
Public Health•
Systematic Review and Meta-analysis of artificial intelligence in classifying HER2 status in breast cancer immunohistochemistry
Oncology•
A Precision Treatment Model for Internet-Delivered Cognitive Behavioral Therapy for Anxiety and Depression Among University Students
Psychiatry•
A practical guide to the implementation of AI in orthopaedic research—Part 7: Risks, limitations, safety and verification of medical AI systems
Orthopedics•
Next-Gen Brain Implants Offer New Hope for Depression
Neurotechnology•
Exploring Artificial Intelligence in Orthopaedics: A Collaborative Survey from the ISAKOS Young Professional Task Force
Orthopedics•
Using Deep Learning With Few-Shot Learning to Improve Data Capture in Total Hip Arthroplasty Operative Notes
Orthopedics•
Insights From Inputs: Enhancing Revision Total Joint Arthroplasty Resource Allocation With Machine Learning Prediction
Orthopedics•
PediaBench: A Comprehensive Chinese Pediatric Dataset for Benchmarking Large Language Models
Pediatrics•
Assisting the infection preventionist: Use of artificial intelligence for health care-associated infection surveillance
Infectious Disease•
Artificial intelligence-based computer aided detection (AI-CAD) in the fight against tuberculosis: Effects of moving health technologies in global health care-associated infection surveillance
Infectious Disease•
The Canadian C-Spine Rule for Radiography in Alert and Stable Trauma Patients
Emergency Medicine•
Efficiency Assessment of Intelligent Patient-Specific Instrumentation in Total Knee Arthroplasty: A Prospective Randomized Controlled Trial
Orthopedics•
Effectiveness of a Conversational Chatbot (Dejal@bot) for the Adult Population to Quit Smoking: Pragmatic, Multicenter, Controlled, Randomized Clinical Trial in Primary Care
Public Health•
Machine-Learning Algorithms to Automate Morphological and Functional Assessments in 2D Echocardiography
Cardiology/Cardiovascular Surgery•
AI-enhanced analysis of naturalistic social interactions characterizes interaffective impairments in schizophrenia
Psychiatry•
Differentiation between atypical anorexia nervosa and anorexia nervosa using machine learning
Psychiatry•
Artificial intelligence based classification and prediction of medical imaging using a novel framework of inverted and self-attention deep neural network architecture
Oncology•
Assessing information provided via artificial intelligence regarding distal biceps tendon repair surgery
Orthopedics•
Artificial intelligence and machine learning on diagnosis and classification of hip fracture: systematic review
Orthopedics•
Deep learning-assisted screening and diagnosis of scoliosis: segmentation of bare-back images via an attention-enhanced convolutional neural network
Orthopedics•
Beyond Traditional Orthopaedic Data Analysis: AI, Multimodal Models and Continuous Monitoring
Orthopedics•
Artificial intelligence demonstrates potential to enhance orthopaedic imaging across multiple modalities: A systematic review
Orthopedics•
An instantaneous voice-synthesis neuroprosthesis
Neurotechnology•
Etomidate versus ketamine for in-hospital rapid sequence intubation: a systematic review and meta-analysis
Emergency Medicine•
Applications of Artificial Intelligence in Ophthalmology: Glaucoma, Cornea, and Oculoplastics
Ophthalmology•
Circadian rhythm modulation in heart rate variability as potential biomarkers for major depressive disorder: A machine learning approach
Psychiatry•
Application and evaluation of artificial intelligence 3D preoperative planning software in developmental dysplasia of the hip
Orthopedics•
Predicting deterioration of ventricular function in patients with repaired tetralogy of Fallot using machine learning
Cardiology/Cardiovascular Surgery•
A Systematic Evaluation of Machine Learning-Based Biomarkers for Major Depressive Disorder
Psychiatry•
Behavioral measures of psychotic disorders: Using automatic facial coding to detect nonverbal expressions in video
Psychiatry•
Association of Early Oseltamivir With Improved Outcomes in Hospitalized Children With Influenza, 2007-2020
Pediatrics•
Artificial intelligence in total and unicompartmental knee arthroplasty
Oncology•
Association of Early Oseltamivir With Improved Outcomes in Hospitalized Children With Influenza, 2007-2020
Pediatrics•
High accuracy but limited readability of large language model-generated responses to frequently asked questions about Kienböck’s disease
Orthopedics•
The Next Frontier in Pediatric Cardiology: Artificial Intelligence
Cardiology/Cardiovascular Surgery•
Chatbots in urology: accuracy, calibration, and comprehensibility; is DeepSeek taking over the throne?
Urology•
Defining ground truth for prostate segmentation of transrectal ultrasound images: Inter‐ and intra‐observer variability of manual versus semi‐automatic methods
Urology•
Artificial Intelligence for Objective Assessment of Pediatric Uroflowmetry Curves.
Urology•
Evaluation of Bladder Dysfunction Outcomes Among Standardized Bladder Shapes in Children With Spina Bifida
Urology•
Hyperspectral Imaging Accurately Detects Renal Malperfusion Due to High Intrarenal Pressure
Urology•
Exploring artificial intelligence in functional urology: A comprehensive review
Urology•
Predicting Extracorporeal Shock Wave Lithotripsy Outcomes Using Machine Learning and the Triple-/Quadruple-D Scores
Urology•
Assessing the impact of AI tools on mobility and daily assistance for children with down syndrome in Saudi Arabia
PM&R•
High-intensity interval training with robotassisted gait therapy vs. treadmill gait therapy in chronic stroke: a randomized controlled trial
PM&R•
Negative prognostic factors and clinical improvement prediction modeling for extracorporeal shockwave therapy in calcific shoulder tendinitis using artificial intelligence techniques
PM&R•
The critical effects of self-management strategies on predicting cancer survivors’ future quality of life and health status using machine learning techniques
PM&R•
Soft robotic gloves versus mirror therapy: a long-term comparative study on hand function and motor recovery in post-stroke rehabilitation
PM&R•
Treatment for Lateropulsion in Standard Clinical Practice: A Multicenter Randomized Controlled Trial
PM&R•
Deep Learning Predicts Postoperative Mobility, Activities of Daily Living, and Discharge Destination in Older Adults from Sensor Data
PM&R•
Preliminary screening of urinary host protein biomarkers for Schistosomiasis haematobium: A proteome profiling study identifying candidate diagnostic targets in school-aged children
Pediatrics•
High content-imaging drug synergy screening identifies specific senescence-related vulnerabilities of mesenchymal neuroblastomas
Pediatrics•
Evaluation of Bladder Dysfunction Outcomes Among Standardized Bladder Shapes in Children With Spina Bifida
Pediatrics•
Portable Electroencephalography in Early Detection of Depression: Progress and Future Directions
Neurotechnology•
Effective Connectivity Predicts Surgical Outcomes in Temporal Lobe Epilepsy: A SEEG Study
Neurotechnology•
EEG-based cerebral pattern analysis for neurological disorder detection via hybrid machine and deep learning approaches
Neurotechnology•
Motor imagery EEG classification method using 3D CNN and LSTM for rehabilitation application
Neurotechnology•
Large language modeling of hallucinatory problem mitigation based on the wheel of emotions
Neurotechnology•
Increased blood-brain barrier permeability is associated with dysfunctional α band connectivity in early-stage Parkinson's disease
Neurotechnology•
Decoding the maxillary morphological mechanism of mid-face depression or protrusion by an interpretable machine learning-assisted approach in an Asian female population
Neurotechnology•
Current Neuroethical Perspectives on Deep Brain Stimulation and Neuromodulation for Neuropsychiatric Disorders: A Scoping Review of the Past 10 Years
Neurotechnology•
AI-Based Localization of the Epileptogenic Zone Using Intracranial EEG
Neurotechnology•
The Role of Quantitative EEG in the Diagnosis of Alzheimer’s Disease
Neurotechnology•
Motor imagery-based brain-computer interfaces: an exploration of multiclass motor imagery-based control for Emotiv EPOC X
Neurotechnology•
Neuroplasticity of Brain Networks Through Exercise: A Narrative Review About Effect of Types, Intensities, and Durations
Neurotechnology•
Neural network-based method for measuring the impacts of epileptic brain activities on cardiac cycles
Neurotechnology•
Exploring the relationship between features calculated from contextual embeddings and EEG band power during sentence reading in Chinese
Neurotechnology•
Enhancing schizophrenia diagnosis efficiency with EEGNet: a simplified recognition model based on γ band features
Neurotechnology•
OpenSpindleNet: An open-source deep learning network for reliable sleep spindle detection in scalp and intracranial EEG
Neurotechnology•
A New Paradigm for Autism Spectrum Disorder Discrimination in Children Utilizing EEG Data Collected During Cartoon Viewing With a Focus on Atypical Semantic Processing
Neurotechnology•
A Deep Learning Approach to Alzheimer’s Diagnosis Using EEG Data: Dual-Attention and Optuna-Optimized SVM
Neurotechnology•
Exploring the relationship between features calculated from contextual embeddings and EEG band power during sentence reading in Chinese
Neurotechnology•
Predicting Metabolic and Cardiovascular Health from Nutritional Patterns and Psychological State Among Overweight and Obese Young Adults: A Neural Network Approach
Neurotechnology•
NeuroFormer: A Deep Learning Framework for Alzheimer’s Detection Using EEG Signals
Neurotechnology•
Identification of Post-Ictal Generalised EEG Suppression with Two-Channel EEG
Neurotechnology•
A Deep Learning Approach to Alzheimer’s Diagnosis Using EEG Data: Dual-Attention and Optuna-Optimized SVM
Neurotechnology•
Alertness assessment by optical stimulation-induced brainwave entrainment through machine learning classification
Neurotechnology•
Recent Advances in Portable Dry Electrode EEG: Architecture and Applications in Brain-Computer Interfaces
Neurotechnology•
Concept2Brain: An AI model for predicting subject-level neurophysiological responses to text and pictures
Neurotechnology•
Deep learning model for detecting cystoid fluid collections on optical coherence tomography in X-linked retinoschisis patients
Ophthalmology•
Use of artificial intelligence in paediatric anesthesia: a systematic review
Ophthalmology•
Recent advances in sMRI and artificial intelligence for presurgical planning in focal cortical dysplasia: A systematic review
Ophthalmology•
Artificial Intelligence Diagnosis of Ocular Motility Disorders from Clinical Videos
Ophthalmology•
Trends and advances in ChatGPT applications in ophthalmology
Ophthalmology•
Comparison of 11 Intraocular Lens Power Calculation Formulas in Eyes Undergoing Simultaneous Cataract Surgery and Descemet Membrane Endothelial Keratoplasty
Ophthalmology•
From visual question answering to intelligent AI agents in ophthalmology
Ophthalmology•
Translating the machine; An assessment of clinician understanding of ophthalmological artificial intelligence outputs
Ophthalmology•
Machine Learning–Based Classification of Depression Using Inflammatory Biomarkers in Pancreatic Cancer Patients
Psychiatry•
The effectiveness of a sentence completion test for depression screening using large language models
Psychiatry•
Predicting Postpartum Depression Risk Using Social Determinants of Health
Psychiatry•
Evaluating chatbots in psychiatry: Rasch-based insights into clinical knowledge and reasoning
Psychiatry•
Childhood trauma and adolescent anxiety: Uncovering emotion regulation pathways through integrated machine learning and traditional statistics
Psychiatry•
AI-Assisted Art Therapy: Enhancing Psychological Recovery in Work-Related Injuries Through Personalized Emotional Support
Psychiatry•
Medication Safety in Acute Care Settings
Medical Informatics•
Innovations in Diabetes Management for Pregnant Women: Artificial Intelligence and the Internet of Medical Things
Medical Informatics•
Feature Selection in Healthcare Datasets: Towards a Generalizable Solution
Medical Informatics•
PED-IA, a CDSS to Support Decision in Pediatrics Telephone Triage: A Crossover Evaluation
Medical Informatics•
Zero-Shot Extraction of Seizure Outcomes from Clinical Notes Using Generative Pretrained Transformers
Medical Informatics•
Integrating multi-source data for skin burn classification using deep learning
Medical Informatics•
When Machines Decide: Exploring How Trust in AI Shapes the Relationship Between Clinical Decision Support Systems and Nurses' Decision Regret: A Cross-Sectional Study
Medical Informatics•
“I Believe That AI Will Recognize the Problem Before It Happens”: Qualitative Study Exploring Young Adults’ Perceptions of AI in Mental Health Care
Psychiatry•
Exposotypes in psychotic disorders
Psychiatry•
A novel approach to smart-assisted schizophrenia screening based on Raman spectroscopy and deep learning
Psychiatry•
A Neural Network Approach to Comparing AMPD and Object Relations Theory for Personality Disorder Assessment
Psychiatry•
The sleep-anxiety dysregulation model of alcohol use disorder risk: A nine-year longitudinal machine learning study
Psychiatry•
Mapping Intersubject Variability in Functional Connectivity in Gray and White Matter to Predict Suicide Risk Among Patients with Major Depressive Disorder
Psychiatry•
An Examination of Generative AI Response to Suicide Inquires: Content Analysis
Psychiatry•
Personalised & Optimised Therapy (POT) Algorithm Using Five Cognitive and Behavioural Skills for Subthreshold Depression
Psychiatry•
Contribution of Chronic Disease in Predicting Depression and Suicidal Ideation Among the Older Adult Population
Psychiatry•
Intervention With Concentrated Albumin for Undifferentiated Sepsis in the Emergency Department (ICARUS-ED): A Pilot Randomized Controlled Trial
Emergency Medicine•
Outcomes and prognostic factors in patients with combined severe traumatic brain injury and abdominal trauma: a retrospective observational study
Emergency Medicine•
Interleukin-6 and its association with outcome in traumatic brain injury: a prospective cohort
Emergency Medicine•
Serum neurofilament light chain and multimodal neuroprognostication after cardiac arrest – A retrospective cohort study
Emergency Medicine•
Effect of Routine Opt-Out HIV Screening on Emergency Department Operational Metrics: Results From the Pragmatic Randomized HIV TESTED Trial
Emergency Medicine•
Optimizing extracorporeal cardiopulmonary resuscitation delivery for out-of-hospital cardiac arrest: a Monte Carlo simulation study
Emergency Medicine•
Remimazolam for procedural sedation in the emergency department: a prospective study of effectiveness and patient satisfaction
Emergency Medicine•
Radiological signs of hypoxic-ischaemic encephalopathy on head computed tomography for prediction of poor functional outcome after cardiac arrest – a prospective observational cohort study
Emergency Medicine•
Exploration of patient blood management metrics for emergency departments: a 4-year retrospective monocenter study
Emergency Medicine•
Comparison of positive expiratory pressure device versus non-invasive ventilation on outcomes in acute exacerbation of chronic obstructive pulmonary disease in the emergency department
Emergency Medicine•
The role of serial point-of-care ultrasound during cardiac arrest to predict termination of resuscitation
Emergency Medicine•
Acidosis as a promising early indicator of mortality among point-of-care parameters and vital sings in non-traumatic critically ill patients
Emergency Medicine•
Ecological and carcinogenic risk assessment of potentially toxic elements in rangelands and croplands around Lake Junin (Peru): Integrating remote sensing, machine learning, and land cover segmentation
Public Health•
Machine learning-based prediction of drinking water quality index in Western Tehran using KAN, MLP, and traditional models
Public Health•
Integrating multiple feature assessment methods to identify key predictors of repeat suicide attempts in Taiwan
Public Health•
Optimizing ambulance location based on road accident data in Rwanda using machine learning algorithms
Public Health•
Perdictive role of the muscle quality index for testosterone deficiency in adult males based on interpretable machine learning methods
Public Health•
The critical effects of self-management strategies on predicting cancer survivors’ future quality of life and health status using machine learning techniques
Public Health•
Mixture of experts for multitask learning in cardiotoxicity assessment.
Public Health•
Natural Language Processing and ICD-10 Coding for Detecting Bleeding Events in Discharge Summaries: Comparative Cross-Sectional Study
Public Health•
Chatbot-Based Version of a World Health Organization–Validated Intervention for Stress Management in Patients With Breast Cancer (Self-Help Plus): Protocol for a Pilot Feasibility Study
Public Health•
Fusion model integrating multi-sequence MRI radiomics and habitat imaging for predicting pathological complete response in breast cancer treated with neoadjuvant therapy
Public Health•
Development and Validation of a Large Language Model–Based System for Medical History-Taking Training: Prospective Multicase Study on Evaluation Stability, Human-AI Consistency, and Transparency
Public Health•
Unveiling causal regulatory mechanisms through cell-state parallax
Public Health•
Longitudinal machine learning prediction of non-suicidal self-injury among Chinese adolescents: A prospective multicenter Cohort study
Public Health•
Explainable deep learning algorithm for distinguishing IVIG-Resistant Kawasaki disease in Shandong peninsula, China
Public Health•
Innovative therapies for diabetic foot ulcers: Application and prospects of smart dressings
Public Health•
Quantifying device type and handedness biases in a remote Parkinson’s disease AI-powered assessment
Public Health•
Cox proportional hazards model with Bayesian neural network for survival prediction
Public Health•
Artificial intelligence for tuberculosis control: a scoping review of applications in public health
Public Health•
A Machine Learning Approach for Identifying People With Neuroinfectious Diseases in Electronic Health Records: Algorithm Development and Validation
Public Health•
Decoding HIV Discourse on Social Media: Large-Scale Analysis of 191,972 Tweets Using Machine Learning, Topic Modeling, and Temporal Analysis
Public Health•
"Using Environmental Mixture Exposure-Triggered Biological Knowledge-Driven Machine Learning to Predict Early Pregnancy Loss"
Public Health•
Evaluation of deep learning models using explainable AI with qualitative and quantitative analysis for rice leaf disease detection
Public Health•
Effects of different AI-driven Chatbot feedback on learning outcomes and brain activity
Neurology•
An explainable AI approach for mapping multivariate regional brain age and clinical severity patterns in Alzheimer’s disease
Neurology•
AI-assisted decision-making in mild traumatic brain injury
Neurology•
Precision Neuro-Oncology in Glioblastoma: AI-Guided CRISPR Editing and Real-Time Multi-Omics for Genomic Brain Surgery
Neurology•
Multivariate whole brain neurodegenerative-cognitive-clinical severity mapping in the Alzheimer’s disease continuum using explainable AI
Neurology•
Predicting Intracranial Hypertension in Traumatic Brain Injury Using AI: A Systematic Review of Algorithms and Their Clinical Integration Potential
Neurology•
Enhance MRI brain tumor detection using deep learning in conjunction with explainable AI SHAP based diverse and multi feature analysis
Neurology•
AI-Assisted Compressed Sensing Enables Faster Brain MRI for the Elderly: Image Quality and Diagnostic Equivalence with Conventional Imaging
Neurology•
Transfer deep learning and explainable AI framework for brain tumor and Alzheimer's detection across multiple datasets
Neurology•
The Redox Revolution in Brain Medicine: Targeting Oxidative Stress with AI, Multi-Omics and Mitochondrial Therapies for the Precision Eradication of Neurodegeneration
Neurology•
Continuous versus intermittent noninvasive blood pressure measurement in patients with shock in prehospital emergency medicine – a single-center prospective pilot trial
Emergency Medicine•
Efficacy of supraglottic airway devices in Chest Compression Synchronized Ventilation during continuous resuscitation: A prospective randomized cross-over cadaver study
Emergency Medicine•
Intravenous Magnesium: Prompt use for Asthma in Children Treated in the Emergency Department (IMPACT-ED), a pilot randomized trial
Emergency Medicine•
Microcosting implementation facilitation for emergency department-initiated buprenorphine for untreated opioid use disorder
Emergency Medicine•
Ultra-early short- and middle-latency SSEP accurately predict good and poor outcome after cardiac arrest
Emergency Medicine•
Diagnostic accuracy of ultrasound and computed tomography in obstructive jaundice at emergency department: a retrospective study
Emergency Medicine•
Mental health and substance use evolution in Swiss ED residents: a 6-month prospective longitudinal single-center study
Emergency Medicine•
Evaluation of Out-of-Hospital Use of a Valsalva Assist Device in the Emergency Treatment of Supraventricular Tachycardia
Emergency Medicine•
Landiolol bolus application for tachycardic dysrhythmia in the prehospital EMS setting – An observational study of a novel concept
Emergency Medicine•
Differentiating Type 1 and Type 2 myocardial infarction using a machine learning algorithm and biomarkers
Emergency Medicine•
High platelet-to-red blood cell ratio and outcomes in trauma patients requiring massive transfusions
Emergency Medicine•
Prediction of infected pancreatic necrosis in patients with acute necrotizing pancreatitis based on ensemble machine learning model
Emergency Medicine•
Atrial Fibrillation Burden Signature and Near-Term Prediction of Stroke: A Machine Learning Analysis
Cardiology/Cardiovascular Surgery•
A Machine-Learning Framework to Identify Distinct Phenotypes of Aortic Stenosis Severity
Cardiology/Cardiovascular Surgery•
State-of-the-art artificial intelligence methods for pre-operative planning of cardiothoracic surgery and interventions: a narrative review
Cardiology/Cardiovascular Surgery•
ECG-Based Deep Learning and Clinical Risk Factors to Predict Atrial Fibrillation
Cardiology/Cardiovascular Surgery•
Cascaded neural network-based CT image processing for aortic root analysis
Cardiology/Cardiovascular Surgery•
Recursive multiresolution convolutional neural networks for 3D aortic valve annulus planimetry
Cardiology/Cardiovascular Surgery•
Machine learning-based mortality prediction of patients undergoing cardiac resynchronization therapy: the SEMMELWEIS-CRT score
Cardiology/Cardiovascular Surgery•
Effectiveness of the GPT-4o Model in Interpreting Electrocardiogram Images for Cardiac Diagnostics: Diagnostic Accuracy Study
Cardiology/Cardiovascular Surgery•
Automatic aortic valve landmark localization in coronary CT angiography using colonial walk
Cardiology/Cardiovascular Surgery•
Artificial Intelligence–Enabled ECGs for Atrial Fibrillation Identification and Enhanced Oral Anticoagulant Adoption: A Pragmatic Randomized Clinical Trial
Cardiology/Cardiovascular Surgery•
Artificial intelligence-assisted diagnosis and prognostication in low ejection fraction using electrocardiograms in inpatient department: a pragmatic randomized controlled trial
Cardiology/Cardiovascular Surgery•
Enabling Automated Device Size Selection for Transcatheter Aortic Valve Implantation
Cardiology/Cardiovascular Surgery•
Artificial intelligence in interventional cardiology: a review of its role in diagnosis, decision-making, and procedural precision
Cardiology/Cardiovascular Surgery•
Machine learning insight into the role of imaging and clinical variables for the prediction of obstructive coronary artery disease and revascularization: An exploratory analysis of the CONSERVE study
Cardiology/Cardiovascular Surgery•
TAVI-PREP: A Deep Learning-Based Tool for Automated Measurements Extraction in TAVI Planning
Cardiology/Cardiovascular Surgery•
Development and Validation of an Artificial Intelligence-Driven Model for Accurate Classification of Erythrodermic Psoriasis Severity: Erythrodermic Psoriasis Integrated Classification System (EPICS)
Dermatology•
Artificial intelligence in total body photography, digital dermoscopy and high-resolution dermoscopy
Dermatology•
A Deep Learning Framework for Automated Early Diagnosis and Classification of Skin Cancer Lesions in Dermoscopy Images
Dermatology•
Ethics of artificial intelligence in dermatology
Dermatology•
Diagnostic performance of artificial intelligence in detecting oral potentially malignant disorders and oral cancer using medical diagnostic imaging: a systematic review and meta-analysis
Dermatology•
Skin cancer segmentation and recognition from dermoscopy images: a novel framework based on improved DeepLabV3+ and network-level fused deep architectures
Dermatology•
Ethics of artificial intelligence in dermatology
Dermatology•
A Deep Learning Framework for Automated Early Diagnosis and Classification of Skin Cancer Lesions in Dermoscopy Images
Dermatology•
Semi-supervised GAN with hybrid regularization and evolutionary hyperparameter tuning for accurate melanoma detection
Dermatology•
Non-invasive optical skin imaging techniques: A historical and contemporary perspective
Dermatology•
Transcriptional dysregulation of skin barrier genes in atopic dermatitis and psoriasis: Mechanistic insights and emerging therapeutic strategies
Dermatology•
CHASHNIt for enhancing skin disease classification using GAN augmented hybrid model with LIME and SHAP based XAI heatmaps
Dermatology•
Deep Learning Modeling to Differentiate Multiple Sclerosis From MOG Antibody-Associated Disease
Neurology•
Phenotypical Differentiation of Tremor Using Time Series Feature Extraction and Machine Learning
Neurology•
Language dysfunction as a primary feature of cognitive decline in neurological populations
Neurology•
Deep Learning for Segmenting Ischemic Stroke Infarction in Non-contrast CT Scans by Utilizing Asymmetry
Neurology•
Temporal basis function models for closed-loop neural stimulation
Neurology•
AlzFormer: Video-based space-time attention model for early diagnosis of Alzheimer's disease
Neurology•
Prediction of intracranial aneurysm rupture from computed tomography angiography using an automated artificial intelligence framework
Neurology•
Exploration of endoplasmic reticulum stress-related gene markers in amyotrophic lateral sclerosis: a comprehensive analysis of bioinformatics and machine learning
Neurology•
Syllable-based speech characteristics as potential biomarker for differential diagnosis of Parkinson’s disease, multiple system atrophy, and cerebellar ataxia
Neurology•
AI-augmented prediction of high-risk PINK1 variants associated with Parkinson's disease: integrating multilayered bioinformatics, MD simulation, and deep learning
Neurology•
Cognitive prediction using regional connectivities and network biomarkers in Alzheimer’s disease
Neurology•
Design and implementation of a writing-stroke motor imagery paradigm for multi-character EEG classification
Neurology•
Redox-Active Polyphenol Red Molecularly Imprinted Polymers on Porous Gold Electrodes for Ultrasensitive, AI-Assisted Detection of Alzheimer's Biomarkers in Undiluted Biofluids
Neurology•
Interictal Epileptiform Discharge; Generative Adversarial Network; LSTM; EEG; convolutional neural network
Neurology•
Federated Transferring Multi-Channel CNN for Diagnosis of Parkinson's Disease under Unseen and Small Data
Neurology•
Knowledge mapping of biomarkers in amyotrophic lateral sclerosis: a comprehensive bibliometric and visual analysis
Neurology•
Prediction of favorable outcomes of acute basilar artery occlusion using machine learning
Neurology•
Artificial Intelligence Approaches for EEG Signal Acquisition and Processing in Lower-Limb Motor Imagery: A Systematic Review
Neurotechnology•
AI-Enabled EEG and Language Models for Obstructive Sleep Apnea Screening
Neurotechnology•
Application of machine learning and temporal response function modeling of EEG data for differential diagnosis in primary progressive aphasia
Neurotechnology•
Ensemble learning techniques reveals multidimensional EEG feature alterations in pediatric schizophrenia
Neurotechnology•
Artificial Intelligence-Guided Neuromodulation in Heart Failure with Preserved and Reduced Ejection Fraction: Mechanisms, Evidence, and Future Directions
Neurotechnology•
Predicting the longitudinal efficacy of medication for depression using electroencephalography and machine learning
Neurotechnology•
Motor imagery‑based neural networks for assisting tetraplegic patients
Neurotechnology•
Use of computer vision analysis for labeling inattention periods in EEG recordings with visual stimuli
Neurotechnology•
Automated sleep staging from single-channel electroencephalogram using hybrid neural network with manual features and attention
Neurotechnology•
Machine Learning-Driven Radiomic Profiling of Thalamus-Amygdala Nuclei for Prediction of Postoperative Delirium After STN-DBS in Parkinson’s Disease Patients: A Pilot Study
Neurotechnology•
Obsessive-compulsive disorder detection using ensemble of scalp EEG-based convolutional neural network
Neurotechnology•
Enhancing classification of a large lower-limb motor imagery EEG dataset for BCI in knee pain patients
Neurotechnology•
NEuroMOrphic Neural-Response Decoding System for Adaptive and Personalized Neuro-Prosthetics' Control
Neurotechnology•
Towards stimulation-free automatic electrocorticographic speech mapping in neurosurgery patients
Neurotechnology•
An interpretable machine learning approach for predicting drug-resistant epilepsy in children with tuberous sclerosis complex
Neurotechnology•
Non-genetic neuromodulation with graphene optoelectronic actuators for disease models, stem cell maturation, and biohybrid robotics
Neurotechnology•
Comparative study of multi-headed and baseline deep learning models for ADHD classification from EEG signals
Neurotechnology•
Decoding the variable velocity of lower-limb stepping movements from EEG
Neurotechnology•
Delineation of the Centromedian Nucleus for Epilepsy Neuromodulation Using Deep Learning Reconstruction of White Matter-Nulled Imaging
Neurotechnology•
From subthalamic local field potentials to the selection of chronic deep brain stimulation contacts in Parkinson's disease - A systematic review
Neurotechnology•
DistillSleep: Real-Time, On-Device, Interpretable Sleep Staging from Single-Channel EEG
Neurotechnology•
Automated Detection of Epileptic Seizures in EEG Signals via Micro-Capsule Networks
Neurotechnology•
Optimized AI-based neural decoding from BOLD fMRI signal for analyzing visual and semantic ROIs in the human visual system
Neurotechnology•
Interpretable machine learning model predicts 1-year inguinal hernia risk after robot-assisted radical prostatectomy
Oncology•
Enhancing Breast Density Assessment in Mammograms Through Artificial Intelligence.
Oncology•
Smart dosing: revolutionizing uveal melanoma treatment with AI.
Oncology•
YOLOv8-BCD: a real-time deep learning framework for pulmonary nodule detection in computed tomography imaging
Oncology•
Development and validation of a machine learning model for predicting immune checkpoint inhibitor efficacy in advanced gastric cancer using dynamic changes in peripheral blood clinlabomics data: a retrospective multicenter cohort study
Oncology•
High transposable element expression in sarcomas is associated with increased immune infiltrates and improved outcomes including after immunotherapy
Oncology•
Improving HER2 Diagnostics with Digital Real-Time PCR for Ultrafast, Precise Prediction of Anti-HER2 Therapy Response in Patients with Breast Cancer
Oncology•
AI to Support Modern Cancer Care—The Augmented Oncologist
Oncology•
Evaluating large language models in neuro-oncology: A comparative study of accuracy, completeness, and clinical usefulness
Oncology•
ChatGPT's role in the rapidly evolving hematologic cancer landscape
Oncology•
Deep learning-based histomorphological subtyping and risk stratification of small cell lung cancer from hematoxylin and eosin-stained whole slide images
Oncology•
DeepPhosPPI: a deep learning framework with attention-CNN and transformer for predicting phosphorylation effects on protein–protein interactions
Oncology•
Sex-Specific Prognostic Value of Automated Epicardial Adipose Tissue Quantification on Serial Lung Cancer Screening Chest CT
Oncology•
AdapTor: Adaptive Topological Regression for quantitative structure-activity relationship modeling
Oncology•
Predicting one-year post-surgical recurrence in colorectal liver metastasis using CT radiomics and machine learning
Oncology•
An MRI–pathology foundation model for noninvasive diagnosis and grading of prostate cancer
Oncology•
Enhanced glioma semantic segmentation using U-net and pre-trained backbone U-net architectures
Oncology•
Exploring potential associations and biomarkers linked polycystic ovarian syndrome with atherosclerosis via comprehensive bioinformatics analysis machine learning and animal experiments.
Oncology•
Deep learning-based prediction of axillary pathological complete response in patients with breast cancer using longitudinal multiregional ultrasound
Oncology•
Multi-omic assessment of mRNA translation dynamics in liver cancer cell lines
Oncology•
DeepMVP: deep learning models trained on high-quality data accurately predict PTM sites and variant-induced alterations
Oncology•
The critical effects of self-management strategies on predicting cancer survivors’ future quality of life and health status using machine learning techniques
Oncology•
A Deep Learning Approach for Tracking Colorectal Cancer-Derived Extracellular Vesicles in Colon and Lung Models
Oncology•
Exploring potential associations and biomarkers linked polycystic ovarian syndrome with atherosclerosis via comprehensive bioinformatics analysis, machine learning, and animal experiments
Oncology•
An artificial intelligence-enhanced early ovarian cancer diagnosis biosensor
Oncology•
Potential role of DKK3 and WIF1 in prostate cancer: bioinformatics and clinical analysis
Oncology•
Artificial intelligence as an independent reader of risk-dominant lung nodules: influence of CT reconstruction parameters
Oncology•
Deep learning-based dual-energy subtraction synthesis from single-energy kV x-ray fluoroscopy for markerless tumor tracking
Oncology•
The immune signatures predict gastric/gastroesophageal junction cancer response to first-line anti-PD-1 blockade or chemotherapy
Oncology•
Artificial Intelligence Diagnosis of Ocular Motility Disorders from Clinical Videos
Ophthalmology•
Machine learning in predicting preoperative intra-aortic balloon pump use in patients undergoing coronary artery bypass grafting
Ophthalmology•
Multimodal deep learning to predict postoperative major adverse cardiac and cerebrovascular events after non-cardiac surgery
Ophthalmology•
Evaluating the novel role of ChatGPT-4 in addressing corneal ulcer queries: An AI-powered insight
Ophthalmology•
Causal inference model for accurate medical diagnosis in Coronary Artery Bypass Graft operation
Ophthalmology•
Evaluating the novel role of ChatGPT-4 in addressing corneal ulcer queries: An AI-powered insight
Opthalmology•
The utility of artificial intelligence in characterization and detecting causes of macular edema: A spectral-domain OCT-based algorithm study
Opthalmology•
Fluid-SegNet: Multi-dimensional loss-driven Y-Net with dilated convolutions for OCT B-scan fluid segmentation
Opthalmology•
Deep learning model for detecting cystoid fluid collections on optical coherence tomography in X-linked retinoschisis patients
Opthalmology•
Comparison of 11 Intraocular Lens Power Calculation Formulas in Eyes Undergoing Simultaneous Cataract Surgery and Descemet Membrane Endothelial Keratoplasty
Opthalmology•
The utility of artificial intelligence in ophthalmic clinical trials
Opthalmology•
Identifying Transportation Needs in Ophthalmology Clinic Notes Using Natural Language Processing: Retrospective, Cross-Sectional Study
Opthalmology•
Translating the machine; An assessment of clinician understanding of ophthalmological artificial intelligence outputs
Opthalmology•
Artificial intelligence coulomics for systemic health and longevity medicine: 2025 and beyond
Opthalmology•
Advancing ophthalmology with large language models: Applications, challenges, and future directions
Opthalmology•
Evaluation of ophthalmic large language models: quantitative vs. qualitative methods
Opthalmology•
Artificial intelligence in opthalmology
Opthalmology•
Shear Wave Optical Coherence Elastography Imaging by Deep Learning
Opthalmology•
DeepSeek-R1 vs OpenAI o1 for Ophthalmic Diagnoses and Management Plans
Opthalmology•
Precision Medicine in Pediatric Attention-Deficit/Hyperactivity Disorder: A Systematic Review of Behavioral, Neurobiological and Genetic Diagnostic Biomarkers
Pediatrics•
How consistent is the interpretation of renal scarring in pediatric patients using technetium-99m dimercaptosuccinic acid scintigraphy
Pediatrics•
A roadmap of artificial intelligence applications in pediatric surgery: a comprehensive review of applications, challenges, and ethical considerations
Pediatrics•
Expert-level differentiation of incomplete Kawasaki disease and pneumonia from echocardiography via multiple large receptive attention mechanisms
Pediatrics•
Neurobehavioral mechanisms of fear and anxiety in multiple sclerosis.
Psychiatry•
Generative Artificial Intelligence Chatbots and Delusions: From Guesswork to Emerging Cases
Psychiatry•
Harnessing artificial intelligence for mental well-being of aging populations
Psychiatry•
Online continuous learning of users suicidal risk on social media
Psychiatry•
Identification and experimental validation of biomarkers related to mitochondrial and programmed cell death in obsessive-compulsive disorder.
Psychiatry•
Demographic and clinical characteristics of patients with borderline personality disorder: Real-world insights from a retrospective observational study
Psychiatry•
Emotion contagion through interaction with generative artificial intelligence chatbots may contribute to development and maintenance of mania
Psychiatry•
A correlation study on EEG signals during visual concentration test and clinical evaluation in schizophrenia patients.
Psychiatry•
Balancing mental health through predictive modeling for healthcare workers during public health crises
Psychiatry•
Distinct Gut Microbial Signatures and Diminished Anti-Inflammatory Effect of Short-Chain Fatty Acids in Schizophrenia With Immune Activation
Psychiatry•
Integrating knowledge: the power of ontologies in psychiatric research and clinical informatics
Psychiatry•
Decoding the adolescent non-suicidal self-injury: understanding with interpretable machine learning insights
Psychiatry•
Algorithmic Fairness in Machine Learning Prediction of Autism Using Electronic Health Records
Psychiatry•
Predicting depression using serum perfluoroalkyl and polyfluoroalkyl substances levels via interpretable machine learning
Psychiatry•
End Users’ Perception on an AI Chatbot in a Snus Cessation Mobile Application
Psychiatry•
Machine learning for novel phenotyping in schizophrenia
Public Health•
Exploring Risk Factors and Predictive Modeling of Child Malnutrition in Pakistan Using Machine Learning
Public Health•
Artificial intelligence approach to optimise safety for hospitalised patients with dementia
Public Health•
Machine learning prediction of clinical pregnancy in endometriosis patients following fresh IVF/ICSI-ET
Public Health•
An AI Model Classifies Risks of Early Relapse Post-CAR T Cell Therapy in a Multi-Center Real-World Population with DLBCL
Public Health•
Predictors of health-related quality of life in older adults over a course of twelve years – Results from a large population-based study using a machine learning approach
Public Health•
Identifying Transportation Needs in Ophthalmology Clinic Notes Using Natural Language Processing: Retrospective, Cross-Sectional Study
Public Health•
From disinfectant to neurodegeneration: Integrating machine learning and mendelian randomization reveals triclosan as a novel environmental risk factor for Alzheimer’s disease
Public Health•
Identifying Firearm Violence Exposure in Primary Care Clinical Notes: Protocol for Developing a National Language Processing Text Classifier
Public Health•
Detection of Visible and Invisible Fecal Contamination on Chicken Carcasses Using Multispectral Fluorescence Imaging and Machine Learning to Mitigate Salmonella Risks
Public Health•
Deciphering Gut Microbiome Dynamics in Irritable Bowel Syndrome Using Deep Learning
Public Health•
DeepGAM: An interpretable deep neural network using generalized additive model for depression diagnosis: Data from the heart and soul study
Public Health•
Respiratory Syncytial Virus Epidemiology and Clinical Burden in High-Risk and ≥ 50-Year-Old Adults in Low- to Middle-Income Countries: An Artificial-Intelligence-Enabled Systematic Literature Review
Public Health•
Nurses Intention to Integrate AI Into Their Practice: Survey Study in Canada
Public Health•
Gender Medicine in Computed Tomography Radiomics Analysis to Predict Disease Progression in Liver Respectable Colorectal Cancer Patients
Public Health•
Analyzing Health Care Professionals’ Resilience and Emotional Responses to COVID-19 via Twitter: Retrospective Cohort and Matched Comparison Group Study
Public Health•
Chatbots in Sexual and Reproductive Health: Bridging the Divide in Accessibility and Equity
Public Health•
Deep aging clocks: AI-powered strategies for biological age estimation
Public Health•
Development and validation of a machine learning-based prediction model for frailty in older adults with diabetes: a study protocol for a retrospective cohort study
Public Health•
Machine learning– and multilayer molecular network–assisted screening hunts fentanyl compounds
Public Health•
Machine learning for predicting the diagnosis of tuberculous versus malignant pleural effusion: External validation and accuracy in two different settings
Public Health•
Deep Learning Modeling to Differentiate Multiple Sclerosis From MOG Antibody–Associated Disease
Public Health•
Genetic rare disease prevention and control: Family-based screening and reproductive interventions in Changsha
OB-GYN•
Exploring potential associations and biomarkers linked polycystic ovarian syndrome with atherosclerosis via comprehensive bioinformatics analysis, machine learning, and animal experiments
OB-GYN•
Artificial Intelligence and Gynecologic Surgery
OB-GYN•
Healthcare professional classification of "poor glucose control" and perinatal outcomes in pregnancies with diabetes: a retrospective cohort study
OB-GYN•
Editorial: Artificial Intelligence in Cardio-Obstetrics — A Technological Leap Toward Safer Pregnancies
OB-GYN•
A comparative evaluation of publicly available large language models in the assessment of CTG traces according to the FIGO criteria
OB-GYN•
Using Environmental Mixture Exposure-Triggered Biological Knowledge-Driven Machine Learning to Predict Early Pregnancy Loss
OB-GYN•
Machine Learning-Based Predictive Model for Fear of Childbirth in Late Pregnancy
OB-GYN•
Flexible ureteroscopy in renal anomalies: an explainable AI model for surgical outcome prediction from EAU endourology
Urology•
Predicting Recurrence After Surgical Resection for High-Risk Localized Renal Cell Carcinoma: A Radiomics Clinical Integration Approach
Urology•
Can ChatGPT pass the urology fellowship examination? Artificial intelligence capability in surgical training assessment
Urology•
Construction and validation of a urinary stone composition prediction model based on machine learning
Urology•
Artificial intelligence in muscle-invasive bladder cancer: opportunities, challenges, and clinical impact
Urology•
Impact of three-dimensional prostate models during robot-assisted radical prostatectomy on surgical margins and functional outcomes
Urology•
Automatic recognition of surgical phase of robot-assisted radical prostatectomy based on artificial intelligence deep-learning model and its application in surgical skill evaluation: a joint study of 18 medical education centers
Urology•
Interpretable machine learning model predicts 1‑year inguinal hernia risk after robot‑assisted radical prostatectomy
Urology•
Deep computer vision with artificial intelligence based sign language recognition to assist hearing and speech-impaired individuals
PM&R•
Harnessing attention-driven hybrid deep learning with combined feature representation for precise sign language recognition to aid deaf and speech-impaired people
PM&R•
Pose2Gaze: Eye-Body Coordination During Daily Activities for Gaze Prediction From Full-Body Poses
PM&R•
Advanced Smart Human Activity Recognition System for Disabled People Using Artificial Intelligence With Snake Optimizer Techniques
PM&R•
Effect of robot-assisted rehabilitation of patients with Parkinson’s disease: A meta-analysis
PM&R•
Feasibility of post-stroke hand rehabilitation supported by a soft robotic hand orthosis in-clinic and at-home
PM&R•
Opinions and Perspectives of Canadian Occupational Therapists on Artificial Intelligence
PM&R•
Accelerating precision exercise medicine in cancer patients using pooled individual patient data: POLARIS experience
PM&R•
ChatGPT as a decision-support tool for better self-monitoring of hearing
PM&R•
An AI-based system for fully automated knee alignment assessment in standard AP knee radiographs
Orthopedics•
Diagnostic value of artificial intelligence-based software for the detection of pediatric upper extremity fractures
Orthopedics•
Predicting Anterior Cruciate Ligament Reconstruction Revision Risk: An Enhanced Machine Learning Analysis of the Danish Knee Ligament Reconstruction Registry
Orthopedics•
Prediction of knee loads during activities of daily living using custom instrumented insoles and machine learning
Orthopedics•
Evaluation of Google and ChatGPT responses to common patient questions about scoliosis
Orthopedics•
Deep learning-based lightweight model for automated lumbar foraminal stenosis classification: sagittal CT diagnostic performance compared to clinical subspecialists
Orthopedics•
Role and potential of artificial intelligence, robotics, and navigation-assisted technologies in the diagnosis, treatment, and prognosis of osteoporotic vertebral compression fractures
Orthopedics•
A comparative study of orthopedic surgeons and AI models in the clinical evaluation of spinal surgery
Orthopedics•
Machine learning-based prediction of the necessity for the surgical treatment of distal radius fractions
Orthopedics•
Systematic Review on Large Language Models in Orthopaedic Surgery
Orthopedics•
Evaluating the Quality and Understandability of Radiology Report Summaries Generated by ChatGPT: Survey Study
Radiology•
Lightweight early detection of knee osteoarthritis in athletes
Orthopedics•
Computational optimization of 3D printed bone scaffolds using orthogonal array-driven FEA and neural network modeling
Orthopedics•
Comparative analysis of machine learning algorithms for predicting tibial intramedullary nail length from patient characteristics
Orthopedics•
Machine learning in predicting preoperative intra-aortic balloon pump use in patients undergoing coronary artery bypass grafting
Cardiology/Cardiovascular Surgery•
Enhancing cognitive state detection through deep Forest-based electroencephalogram signal analysis and classification
Neurotechnology•
Neuroimaging Correlates of Post-Stroke Pain After Ischemic Stroke: Secondary Analysis of the INSPiRE-TMS Trial
Neurotechnology•
Optimized AI-based neural decoding from BOLD fMRI signal for analyzing visual and semantic ROIs in the human visual system
Neurotechnology•
PicoSleepNet: An Ultra Lightweight Sleep Stage Classification by Spike Neural Network using Single-channel EEG Signal
Neurotechnology•
Detection and Recognition of Bilingual Urdu and English Text in Natural Scene Images Using a Convolutional Neural Network-Recurrent Neural Network Combination with a Connectionist Temporal Classification Decoder
Neurotechnology•
Recurrence affects the geometry of visual representations across the ventral visual stream in the human brain
Neurotechnology•
Enhancing cognitive state detection through deep Forest-based electroencephalogram signal analysis and classification
Neurotechnology•
Lightweight self-attention and deep gated neural network (LSA-DGNet) for multiple neurological disease detection
Neurotechnology•
Unveiling multi-domain signatures of EEG oscillations using a fully-interpretable convolutional neural network
Neurotechnology•
Directional hand movement can be classified from insular cortex SEEG signals using recurrent neural networks and high-gamma band features
Neurotechnology•
A novel ANN-based classification of spike-wave activity in 24-hour EEG recordings in rats using spectrograms: Spike-Wave Discharge Artificial Neural Network (SWAN)
Neurotechnology•
Optimal Stimulation Sites and Connectomes for GPi and STN‐DBS in Cervical Dystonia
Neurotechnology•
Spatiospectral Representation and Neural Decoding of Somatic Perception of Acupuncture Stimulations
Neurotechnology•
EEG-Based Authentication Across Various Event-Related Potentials (ERPs)
Neurotechnology•
A Multi-Branch Network for Integrating Spatial, Spectral, and Temporal Features in Motor Imagery EEG Classification
Neurotechnology•
Feature fusion ensemble classification approach for epileptic seizure prediction using electroencephalographic bio-signals
Neurotechnology•
Multi-Scale Temporal Fusion Network for Real-Time Multimodal Emotion Recognition in IoT Environments
Neurotechnology•
BrainVision: Cross-domain EEG decoding for visual content retrieval and reconstruction
Neurotechnology•
RDPNet: A Multi-Scale Residual Dilated Pyramid Network with Entropy-Based Feature Fusion for Epileptic EEG Classification
Neurotechnology•
Brain–Computer Interface for EEG-Based Authentication: Advancements and Practical Implications
Neurotechnology•
Where do I go? Decoding temporal neural dynamics of scene processing and visuospatial memory interactions using convolutional neural networks
Neurotechnology•
Integrating Cortical Source Reconstruction and Adversarial Learning for EEG Classification
Neurotechnology•
A Sparse-Integrated Filtering Residual Spiking Neural Network for High-Accuracy Spike Sorting and Co-optimization on Memristor Platforms
Neurotechnology•
A novel fuzzy deep learning network for electroencephalogram classification of major depressive disorder
Neurotechnology•
Optimized XGBoost for Multimodal Affective State Classification Using In-Ear PPG and Behind-the-Ear EEG Signals
Neurotechnology•
Lightweight self-attention and deep gated neural network (LSA-DGNet) for multiple neurological disease detection
Neurotechnology•
Artificial intelligence-based action recognition and skill assessment in robotic cardiac surgery simulation: a feasibility study
Cardiology/Cardiovascular Surgery•
Deep learning for echocardiographic assessment and risk stratification of aortic, mitral, and tricuspid regurgitation: the DELINEATE-regurgitation study
Cardiology/Cardiovascular Surgery•
Artificial intelligence predictive analytics in heart failure: results of the pilot phase of a pragmatic randomized clinical trial
Cardiology/Cardiovascular Surgery•
Blinded, randomized trial of sonographer versus AI cardiac function assessment
Cardiology/Cardiovascular Surgery•
AI-based prediction of left bundle branch block risk post-TAVI using pre-implantation clinical parameters
Cardiology/Cardiovascular Surgery•
Automated analysis of cardiovascular magnetic resonance myocardial native T1 mapping images using fully convolutional neural networks
Cardiology/Cardiovascular Surgery•
Current trends and future prospects of language models and processing systems in spine surgery – a scoping review
Orthopedics•
Prediction of biomechanical properties of ex vivo human femoral cortical bone using Raman spectroscopy and machine learning algorithms
Orthopedics•
AI-Assisted Design and Evaluation of SLM-Ti64 Implants for Enhanced Bone Regeneration
Orthopedics•
LASSO-based machine learning algorithm for prediction of dysphagia in patients suffering anterior cervical discectomy and fusion
Orthopedics•
Recent advancements in personalized management of prostate cancer biochemical recurrence after radical prostatectomy
Urology•
Artificial Intelligence-Based Analysis of Uroflowmetry Patterns in Children: A Machine Learning Perspective
Urology•
Comparative analysis of machine learning-derived nomogram and biomarkers in predicting side-specific extraprostatic extension: Preliminary findings
Urology•
Deep Learning–Based Pattern Recognition for Detecting Penile Abnormalities: Protocol for Developing a Mobile App for Circumcision Eligibility
Urology•
Accuracy, Clarity, and Comprehensiveness of ChatGPT Outputs for Commonly Asked Questions About Living Kidney Donation
Urology•
Evaluating the Performance of Large Language Models on Multispecialty FRCS Section 1 Questions
Urology•
Toward Sex-Specific Biomaterials Innovation: A Perspective
Urology•
Conversational AI Phone Calls to Support Patients With Atrial Fibrillation: Randomized Controlled Trial
PM&R•
Deep Learning Predicts Postoperative Mobility, Activities of Daily Living, and Discharge Destination in Older Adults from Sensor Data
PM&R•
Feasibility and Acceptance of a Remotely Supervised Home-Based Group Mobility Exercise for Older Adults Using a Mobile Robotic Telepresence: A Pilot Study
PM&R•
Artificial Intelligence Approaches for EEG Signal Acquisition and Processing in Lower-Limb Motor Imagery: A Systematic Review
PM&R•
AI and stroke rehabilitation: the past, present and future
PM&R•
Geographic environments, daily activities and stress in Luxembourg (the FragMent study): a protocol combining map-based questionnaires, geographically explicit ecological momentary assessment and vocal biomarkers of stress
PM&R•
Towards safe and efficient preoperative planning of transcatheter mitral valve interventions
Cardiology/Cardiovascular Surgery•
Artificial Intelligence for Detection of Cardiovascular-Related Diseases from Wearable Devices: A Systematic Review and Meta-Analysis
Cardiology/Cardiovascular Surgery•
A second-generation artificial intelligence-based therapeutic regimen improves diuretic resistance in heart failure: Results of a feasibility open-labeled clinical trial
Cardiology/Cardiovascular Surgery•
Artificial Intelligence in Depression–Medication Enhancement (AID-ME): A Cluster Randomized Trial of a Deep-Learning-Enabled Clinical Decision Support System for Personalized Depression Treatment Selection and Management
Medical Informatics•
External Exposome Factors and Adverse Heart Failure Outcomes in the OneFlorida+ Network: Retrospective Cohort Study
Medical Informatics•
Artificial intelligence and perspective for rare genetic kidney diseases
Medical Informatics•
Prediction Model of Intradialytic Hypertension in Hemodialysis Patients Based on Machine Learning
Public Health•
Artificial intelligence, digital media, and population health: Exposure science and social determinants of health
Public Health•
Crowdsourcing a Training Dataset of Question-and-Answer Pairs for AI-Enabled Health Information Tools on Sexually Transmitted Infections: Protocol for a Cross-Sectional Exploratory Survey Study
Public Health•
Reducing Hallucinations and Trade-Offs in Responses in Generative AI Chatbots for Cancer Information: Development and Evaluation Study
Public Health•
Extracting Symptoms of Complex Conditions from Online Discourse (Subreddit to Symptomatology): Lexicon-Based Approach
Public Health•
Generative artificial intelligence in otorhinolaryngology: From innovation to public health transformation
Public Health•
Prognostic models for radiation‐induced complications after radiotherapy in head and neck cancer patients
Public Health•
Predicting Unplanned Readmission Risk in Patients With Cirrhosis: Complication-Aware Dynamic Classifier Selection Approach
Public Health•
Machine Learning-Based Prediction Model for Health-Related Quality of Life in Diabetic Patients
Public Health•
Assessing Heterogeneity in Sentiment Changes in Text-Based Counseling: Latent Class Trajectory Analysis
Public Health•
The application of robotic and artificial intelligence technologies in spinal surgery: a review focused on prospects in remote areas of China
Public Health•
Prediction Model of Intradialytic Hypertension in Hemodialysis Patients Based on Machine Learning
Public Health•
Prevalence and Risk Factors of Suicidal Ideation Amongst Unaccompanied Young Refugees: A Machine Learning Approach
Public Health•
Advancing the Safe Motherhood Initiative: A Qualitative and Sentiment Analysis of Local Physician’s Perspectives on Antibiotic Self-Medication During Pregnancy in a Low- and Middle-Income Country
Public Health•
Predicting the Future Risk and Outcomes of Severe Heart Failure and Coronary Artery Disease With Machine Learning in the UK Biobank Cohort
Public Health•
Real-World Evaluation of AI-Driven Diabetic Retinopathy Screening in Public Health Settings: Validation and Implementation Study
Public Health•
Health-Related Concerns of Anti-LGBTQ+ Legislation: Thematic Analysis Using Social Media Data
Public Health•
New Opportunities for Health and Resilience Measures for Suicide Prevention (NO HARMS): protocol to investigate suicidal behaviours using linked multisystem administrative data
Public Health•
Advancing basal cell carcinoma diagnosis: Insights and gaps in line-field confocal optical coherence tomography
Dermatology•
Large-Scale Dermatopathology Dataset for Lesion Segmentation: Model Development and Analysis
Dermatology•
Artificial Intelligence in Contact Dermatitis: Current and Future Perspectives
Dermatology•
Asynchronous and focal federated learning for skin lesion classification under local data scarcity and class imbalance
Dermatology•
Diagnostic Accuracy of ChatGPT in Dermatology: A Meta-Analysis of Textual versus Visual Prompts
Dermatology•
Identifying melanoma among benign simulators – Is there a role for deep learning convolutional neural networks?
Dermatology•
3D total body photography, a promising innovation for early skin cancer detection: scoping review
Dermatology•
Enhancing Skin Disease Diagnosis: Interpretable Visual Concept Discovery with SAM
Dermatology•
A perspective on integrating digital pathology, proteomics, clinical data and AI analytics in cancer research
Dermatology•
Artificial intelligence in medical imaging empowers precision neoadjuvant immunochemotherapy in esophageal squamous cell carcinoma
Dermatology•
Performance of mental health chatbot agents in detecting and managing suicidal ideation
Psychiatry•
Discovery of factors associated with smartphone addiction among high school adolescents: Using machine learning and network analysis
Psychiatry•
Prediction of treatment outcome in bipolar disorder: when can we expect clinical relevance?
Psychiatry•
Brain connectome differences between attention deficit hyperactivity disorder (ADHD) and neurotypical children during visual attention: A study using a minimum spanning tree graph, multichannel EEG recording and machine learning
Psychiatry•
Artificial intelligence-assisted visual elicitation in anorexia nervosa
Psychiatry•
Artificial intelligence driven neuropsychiatry: a systematic review of electroencephalography-based computational techniques for major depressive disorder prediction
Psychiatry•
Toward a fair, gender-debiased classifier for the diagnosis of attention deficit/hyperactivity disorder- a Machine-Learning based classification study.
Psychiatry•
Machine-Learning-Based Prediction of Suicide Risk Using Preliminary Questionnaire and Consultation Text
Psychiatry•
The problem of atypicality in LLM-powered psychiatry
Psychiatry•
A deep learning model for diagnosing autism using brain time series
Psychiatry•
Predicting factors associated with anxiety by patients undergoing treatment for infectious diseases using a random-forest machine learning approach
Psychiatry•
Chronic Pain Prevalence, Opioid Use, and Primary Care Provider Opioid Prescription Patterns in the U.S. from 2017 to 2019 Derived from Medicaid Claims Data
Psychiatry•
THLANet: A deep learning framework for predicting TCR-pHLA binding in immunotherapy applications
Oncology•
Identifying melanoma among benign simulators – Is there a role for deep learning convolutional neural networks? (MelSim Study)
Oncology•
Gene context drift identifies drug targets to mitigate cancer treatment resistance
Oncology•
NeXtBrain: Combining local and global feature learning for brain tumor classification
Oncology•
Development and Validation of a Cell-Free DNA Fragmentomics–Based Model for Early Detection of Pancreatic Cancer
Oncology•
Artificial Intelligence in Ocular Transcriptomics: Applications of Unsupervised and Supervised Learning
Opthalmology•
Advancing ophthalmology with large language models: Applications, challenges, and future directions
Opthalmology•
Diagnostic and Screening AI Tools in Brazil’s Resource-Limited Settings: Systematic Review
Opthalmology•
Deep Learning–Based Detection of Papilledema on Retinal Photographs From Handheld Cameras: A Prospective Study
Opthalmology•
Assessing accuracy, readability & reliability of AI-generated patient leaflets on Descemet membrane endothelial keratoplasty
Opthalmology•
Systematic review of cost effectiveness and budget impact of artificial intelligence in healthcare
Opthalmology•
Artificial Intelligence in Ophthalmology: Acceptance, Clinical Integration, and Educational Needs in Switzerland
Opthalmology•
Artificial intelligence in pediatric healthcare: current applications, potential, and implementation considerations
Pediatrics•
Detection of neonatal pneumoperitoneum on radiographs using deep multi-task learning
Pediatrics•
Comparison of dengue, chikungunya, and Zika among children in Nicaragua across 18 years: a single-centre, prospective cohort study
Pediatrics•
Deciphering the unique autoregulatory mechanisms and substrate specificity of the understudied DCLK3 kinase linked to neurodegenerative diseases
Neurology•
Analysis of Freezing of Gait in Parkinson's Disease Detection Using a Multimodal Prototype Learning Framework
Neurology•
Neural correlates of forward and backward walking in MS: insights from myelin water imaging
Neurology•
Integrated machine learning-based RNA sequencing and single-cell analysis reveal RNA methylation regulation patterns in the immune microenvironment of Alzheimer's disease
Neurology•
Genetic and Mechanistic Insights Inform Amyotrophic Lateral Sclerosis Treatment and Symptomatic Management: Current and Emerging Therapeutics and Clinical Trial Design Considerations
Neurology•
A Preliminary Study on an Intelligent Segmentation and Classification Model for Amygdala-Hippocampus MRI Images in Alzheimer’s Disease
Neurology•
Artificial intelligence in headache medicine: between automation and the doctor-patient relationship. A systematic review
Neurology•
Role of Morbidity Clusters in Midlife on Ischemic Stroke Incidence and Severity: The ARIC Study
Neurology•
Interpretable Artificial Intelligence Analysis of Functional Magnetic Resonance Imaging for Migraine Classification: Quantitative Study
Neurology•
An Engineered Supramolecular Fluorescent Chemosensor for Multiscale Visualization of Glutamate Dynamics in Living Systems
Neurology•
Automated rating of Fazekas scale in fluid-attenuated inversion recovery MRI for ischemic stroke or transient ischemic attack using machine learning
Neurology•
SpinalTRAQ: A novel pipeline for volumetric cervical spinal cord analysis identifies the corticospinal tract synaptic projectome in healthy and post-stroke mice
Neurology•
Artificial Intelligence for Alzheimer's disease diagnosis through T1-weighted MRI: A systematic review
Neurology•
Use of proper orthogonal decomposition and machine learning for efficient blood flow prediction in cerebral saccular aneurysms
Neurology•
Detection of Microscopic Glioblastoma Infiltration in Peritumoral Edema Using Interactive Deep Learning With DTI Biomarkers: Testing via Stereotactic Biopsy
Neurology•
Stroke-Aware CycleGAN: Improving Low-Field MRI Image Quality for Accurate Stroke Assessment
Neurology•
Comparison of the incidence of recovery agitation with two different doses of ketamine in procedural sedation: A randomized clinical trial
Emergency Medicine•
Presentation of gastrointestinal bleeding in patients with antithrombotic therapy, results from a consecutive retrospective cohort
Emergency Medicine•
Performance of ChatGPT, Gemini and DeepSeek for non-critical triage support using real-world conversations in emergency department
Emergency Medicine•
Randomized Controlled Trial of Atorvastatin in Acute Influenza in the Emergency Department
Emergency Medicine•
Hypoxemia in trauma patients receiving two different oxygen strategies: a TRAUMOX2 substudy
Emergency Medicine•
Piroxicam and paracetamol in the prevention of early recurrent pain and emergency department readmission after renal colic: Randomized placebo-controlled trial
Emergency Medicine•
Diastolic blood pressures and end tidal carbon dioxides during cardiopulmonary resuscitations and their association with outcomes in adult out-of-hospital cardiac arrest patients: A preplanned secondary analysis of the Augmented Medication CardioPulmonary resuscitation (AMCPR) trial
Emergency Medicine•
Factors associated with 30-day drug-related emergency department re-attendance among methamphetamine users: a territory-wide retrospective study in Hong Kong
Emergency Medicine•
Out-of-Hospital Intranasal Ketamine as an Adjunct to Fentanyl for the Treatment of Acute Traumatic Pain: A Randomized Clinical Trial
Emergency Medicine•
Long guidewire peripheral intravenous catheters in emergency departments for management of difficult intravenous access: A multicenter, pragmatic, randomized controlled
Emergency Medicine•
Artificial Intelligence- Enabled Quantitative Coronary Plaque and Hemodynamic for Predicting Acute Coronary Syndrome
Cardiology/Cardiovascular Surgery•
Automated Assessment of Cardiac Systolic Function From Coronary Angiograms With Video-Based Artificial Intelligence Algorithms
Cardiology/Cardiovascular Surgery•
Detection of Hypertrophic Cardiomyopathy Using a Convolutional Neural Network-Enabled Electrocardiogram
Cardiology/Cardiovascular Surgery•
Toward Replacing Late Gadolinium Enhancement With Artificial Intelligence Virtual Native Enhancement for Gadolinium-Free Cardiovascular Magnetic Resonance Tissue Characterization in Hypertrophic Cardiomyopathy
Cardiology/Cardiovascular Surgery•
Development and validation of multicentre study on novel Artificial Intelligence-based Cardiovascular Risk Score (AICVD)
Cardiology/Cardiovascular Surgery•
Fully Automated Echocardiogram Interpretation in Clinical Practice
Cardiology/Cardiovascular Surgery•
Automated Echocardiographic Detection of Severe Coronary Artery Disease Using Artificial Intelligence
Cardiology/Cardiovascular Surgery•
Utility of Multiclass Machine Learning Algorithms in Predicting Same-Day Discharge Following Primary Total Knee Arthroplasty
Orthopedics•
DCE-UNet: A Transformer-Based Fully Automated Segmentation Network for Multiple Adolescent Spinal Disorders in X-ray Images
Orthopedics•
Deep Learning for Automated 3D Assessment of Rotator Cuff Muscle Atrophy and Fat Infiltration prior to Total Shoulder Arthroplasty
Orthopedics•
A comprehensive deep learning approach to improve enchondroma detection on X-ray images
Orthopedics•
MV2SwimNet: A lightweight transformer-based hybrid model for knee meniscus tears detection
Orthopedics•
AI-Powered Smartphone Application for Measuring Hallux Valgus Angle From Radiographs Displayed on a Monitor
Orthopedics•
A Computer Vision and Machine Learning Approach to Classify Views in Distal Radius Radiographs
Orthopedics•
A Deep Learning Tool for Hip Minimum Joint Space Width Calculation on Antero-posterior Pelvis Radiographs
Orthopedics•
Investigating ACL length, strain and tensile force in high impact and daily activities through machine learning
Orthopedics•
AI in Instrumental Gait Analysis and Solution Approaches
Orthopedics•
Impact of prompting on large language model performance: ChatGPT-4 performance on the 2023 hand surgery self-assessment examination
Orthopedics•
Assessing the ability of large language models to simplify lumbar spine imaging reports into patient-facing text: a pilot study of GPT-4
Orthopedics•
Improving Prediction of Fragility Fractures in Postmenopausal Women using Random Forest
Orthopedics•
Machine Learning Model for Selection of Cementless Total Knee Arthroplasty Candidates Utilizing Patient and Radiographic Parameters
Orthopedics•
Caution Regarding ChatGPT’s Appropriateness and Reliability Regarding Surgery for Wrist Arthritis
Orthopedics•
Predicting opioid consumption after surgical discharge: a multinational derivation and validation study using a foundation model.
Orthopedics•
Analysis of potential molecular targets and mechanisms of brominated flame retardants in causing osteoarthritis using network toxicology, machine learning, SHAP analysis, and molecular dynamics simulation
Orthopedics•
Patient education strategies in pediatric orthopaedics: using ChatGPT to answer frequently asked questions on scoliosis
Orthopedics•
Advancements in deep learning-based image screening for orthopedic conditions: Emphasis on osteoporosis, osteoarthritis, and bone tumors
Orthopedics•
Developing a three-dimensional convolutional neural network for automated full-volume multi-tissue segmentation of the shoulder with comparisons to Goutallier classification and partial volume muscle quality analysis
Orthopedics•
Evaluation of the accuracy of ChatGPT in answering asthma-related questions
Public Health•
Artificial intelligence and infectious diseases: tackling antimicrobial resistance, from personalised care to antibiotic discovery
Public Health•
The utility of artificial intelligence in the management of dengue fever: a perspective on future directions
Public Health•
The intersection of artificial intelligence with qualitative or mixed methods for communicable disease research: a scoping review
Public Health•
Identifying Predictors of Problematic Substance Use Among Youth Living with HIV in Uganda: A Machine Learning Approach
Public Health•
Large Language Models’ Clinical Decision-Making on When to Perform a Kidney Biopsy: Comparative Study
Public Health•
Automated Detection and Prediction of Suicidal Behavior From Clinical Notes Using Deep Learning
Public Health•
Social Media Recruitment in Indigenous and Native American Populations: Challenges in the AI Age
Public Health•
Understanding and Addressing Challenges With Electronic Health Record Use in Gynecological Oncology: Cross-Sectional Survey of Multidisciplinary Professionals in the United Kingdom and Co-Design of an Integrated Informatics Platform to Support Clinical Decision-Making
Public Health•
Harnessing artificial intelligence for enhanced public health surveillance: a narrative review
Public Health•
Artificial intelligence and infectious diseases: an evidence-driven conceptual framework for research, public health, and clinical practice
Public Health•
Revisiting the social determinants of health with explainable AI: a cross-country perspective
Public Health•
Supervised machine learning for classification and prediction of stunting among under-five Egyptian children
Public Health•
Artificial Intelligence in Cardiovascular Health: Insights into Post-COVID Public Health Challenges
Public Health•
Real-time activity and fall detection using transformer-based deep learning models for elderly care applications
Public Health•
Three-layered semantic framework for public health intelligence
Public Health•
Application of machine learning for early detection of chronic diseases in Africa
Public Health•
Predicting the risk of COVID-19 among adult patients with diabetes: A machine learning approach
Public Health•
AI4PEP: strengthening public health systems through the responsible application of artificial intelligence — lessons from the Dominican Republic
Public Health•
Automated sepsis prediction from unstructured electronic health records using natural language processing: a retrospective cohort study
Public Health•
"Interpretable Machine Learning for Predicting Adverse Pregnancy Outcomes in Gestational Diabetes: Retrospective Cohort Study"
Public Health•
Development of a Data-Based Method for Predicting Nursing Workload in an Acute Care Hospital: Methodological Study
Public Health•
Robotics, artificial intelligence, telepresence, and telesurgery: The future of urology
Urology•
Identifying Predictors of Cervical Cancer Screening Uptake in Sub-Saharan Africa Using Machine Learning: Cross-Sectional Study
Urology•
Artificial Intelligence in the Business of Urology
Urology•
Integration of Generative Artificial Intelligence into Urological Practice: A Cross-Sectional Survey Analysis from the EAU Endourology
Urology•
Development and validation of an explainable machine learning model for predicting sepsis risk following flexible ureteroscopic lithotripsy
Urology•
Enhancing AI-enabled LLMs in urolithiasis and urology: from ChatGPT through deepseek to fusion and collaboration LLMs
Urology•
Stroke Telerehabilitation Through AI-based Motion Capture and Exergaming
PM&R•
An exploration of the use of artificial intelligence to supplement activity performance in acquired brain injury: a single case experimental design
PM&R•
Artificial intelligence for a diagnosing rare bone diseases: a global survey of healthcare professionals
PM&R•
Real-time activity and fall detection using transformer-based deep learning models for elderly care applications
PM&R•
Implantable Neural Speech Decoders: Recent Advances, Future Challenges
PM&R•
Artificial Intelligence and Applications in PM&R
PM&R•
The Role of ChatGPT in osteoporosis management: a comparative analysis with clinical expertise
PM&R•
From Pathophysiology to Innovative Therapies in Eye Diseases: A Brief Overview
Opthalmology•
Global trends in retinal vein occlusion studies from 2004 to 2023: a bibliometric analysis
Opthalmology•
Artificial intelligence-driven patient history and symptoms combined with slit-lamp eye stimulation for enhancing the clinical training of students
Opthalmology•
Dual site external validation of artificial intelligence-enabled treatment monitoring for neovascular age-related macular degeneration in England
Opthalmology•
Novel artificial intelligence applications for pediatric retina
Opthalmology•
Decision Tree Modeling to Predict Myopia Progression in Children Treated with Atropine: Toward Precision Ophthalmology
Opthalmology•
Self-AttentionNeXt: Exploring schizophrenic optical coherence tomography image detection investigations.
Opthalmology•
Real-time video-based gaze tracking for detecting subtle changes in the deviation angle of the abducens nerve in abducens nerve palsy.
Opthalmology•
OcuViT: A Vision Transformer-Based Approach for Automated Diabetic Retinopathy and AMD Classification
Opthalmology•
Blind Source Separation-Embedded Electroencephalogram Microstate Trajectory Modeling for Generalized Anxiety Disorder Identification
Neurotechnology•
Differentiation of tumor versus peritumoral cortex in gliomas by intraoperative electrocorticography
Neurotechnology•
The Boston Children's Hospital Sleep Corpus: A Collection of 15,695 Annotated Pediatric Polysomnograms
Neurotechnology•
Fiber Memristor-Based Physical Reservoir Computing for Multimodal Sleep Monitoring
Neurotechnology•
Artificial intelligence in preclinical epilepsy research: Current state, potential, and challenges
Neurotechnology•
Exploring the Morphological Study of the Brain in Patients with Bipolar Disorder Based on Structural Magnetic Resonance Imaging
Neurotechnology•
Data fusion of medical imaging in neurological disorders
Neurotechnology•
LFSP-DSM: A Lightweight Framework for Seizure Prediction Based on Deep Statistical Model
Neurotechnology•
A robust deep learning-driven framework for detecting Parkinson’s disease using EEG
Neurotechnology•
Building hybrid models of neuromodulation from automatic segmentation of peripheral nerve histological sections
Neurotechnology•
A hybrid quorum sensing model for neurodynamic feature optimization in EEG-based Parkinson's disease detection
Neurotechnology•
Deep learning applied in epilepsy: Bibliometric and visual analysis
Neurotechnology•
Multitarget neurostimulation of the deep brain: clinical opportunities, challenges, and emerging technologies
Neurotechnology•
Temporal basis function models for closed-loop neural stimulation
Neurotechnology•
Deep feature extraction and swarm-optimized enhanced extreme learning machine for motor imagery recognition in stroke patients
Neurotechnology•
Multi-Channel Fusion Deep Wavelet Spectrum Network for Epileptic Signal Classification
Neurotechnology•
Neuroengineering Approaches Assessing Structural and Functional Changes of Motor Descending Pathways in Stroke
Neurotechnology•
Behavior Decoding Delineates Seizure Microfeatures and Associated Sudden Death Risks in Mouse Models of Epilepsy
Neurotechnology•
Differential modulation of movement speed with state-dependent deep brain stimulation in Parkinson’s disease
Neurotechnology•
From Brain to Being: Reintegrating Philosophy Into Neurology Education
Neurotechnology•
Brainwide hemodynamics predict EEG neural rhythms across sleep and wakefulness in humans
Neurotechnology•
Selection of representative electrodes for stereoscopic visual comfort studies in conjunction with brain mechanism analysis
Neurotechnology•
HBUED: An EEG dataset for emotion recognition
Neurotechnology•
Impulsivity in cerebellar ataxia: an online, multidimensional assessment
Neurology•
Application of Deep Learning for Predicting Hematoma Expansion in Intracerebral Hemorrhage Using Computed Tomography Scans: A Systematic Review and Meta-Analysis of Diagnostic Accuracy
Neurology•
3D-CNN Enhanced Multiscale Progressive Vision Transformer for AD Diagnosis
Neurology•
Behavioral timing of interictal spikes, but not rate, correlates with impaired working memory performance.
Neurology•
Peripheral innate immune signature links migraine and depression: Identification of PTX3 and HP as shared diagnostic biomarkers
Neurology•
Artificial Intelligence-Powered Quantification of Flortaucipir PET for Detecting Tau Pathology
Neurology•
AI-assisted detection of cerebral aneurysms on 3D time-of-flight MR angiography: User variability and clinical implications
Neurology•
AI Based Clinical Decision-Making Tool for Neurologists in the Emergency Department
Neurology•
Enhancing Automated Seizure Detection via Self-Calibrating Spatial-Temporal EEG Features with SC-LSTM
Neurology•
The best diagnostic approach for classifying ischemic stroke onset time: A systematic review and meta-analysis
Neurology•
Deep feature extraction and swarm-optimized enhanced extreme learning machine for motor imagery recognition in stroke patients
Neurology•
Potential of ChatGPT in youth mental health emergency triage: Comparative analysis with clinicians.
Psychiatry•
Reliability and validity of artificial intelligence-based innovative digital scale for the assessment of anxiety in children
Psychiatry•
Immunometabolic Pathways: Investigating Mediators of Major Depressive Disorder and Atherosclerotic Cardiovascular Disease Comorbidity
Psychiatry•
Automated detection and prediction of suicidal behavior from clinical notes using deep learning
Psychiatry•
Cross-jurisdictional factors linked to gambling frequency in adolescents from 28 European countries: a machine learning approach
Psychiatry•
Machine learning algorithms and their predictive accuracy for suicide and self-harm: Systematic review and meta-analysis
Psychiatry•
Public perception and changing attitudes toward antidepressants over a decade in social media: Lessons learned from online discussion using artificial intelligence
Psychiatry•
Impulsivity and neuroticism share distinct functional connectivity signatures with alcohol-use risk in youth
Psychiatry•
Predicting Suicide Using Natural Language Processing of Autobiographical Memory
Psychiatry•
Machine learning for novel phenotyping in schizophrenia
Psychiatry•
High-resolution mapping of alcohol-related brain connectivity in adults using 7T fMRI and multivoxel pattern classification
Psychiatry•
The coming era of nudge drugs for cancer
Oncology•
Differentiation of tumor versus peritumoral cortex in gliomas by intraoperative electrocorticography
Oncology•
DNA methylation-based classification of kidney neoplasms
Oncology•
A Multicenter Pivotal Study on the Artificial Intelligence System for Neoplastic Lesions Detection in Upper Gastrointestinal Endoscopy
Oncology•
Challenging the Status Quo Regarding the Benefit of Chest Radiographic Screening
Oncology•
Flexynesis: A deep learning toolkit for bulk multi-omics data integration for precision oncology and beyond
Oncology•
Histopathological Image Analysis and Enhanced Diagnostic Accuracy Explainability for Oral Cancer Detection
Oncology•
MorphoITH: a framework for deconvolving intra-tumor heterogeneity using tissue morphology
Oncology•
Quantitative and spatial distribution characteristics of CD66b+ tumor-associated neutrophils in metaplastic and non-metaplastic triple-negative breast cancer treated with neoadjuvant therapy and their prognostic significance
Oncology•
Automated Kidney Tumor Segmentation in CT Images Using Deep Learning: A Multi-Stage Approach
Oncology•
Vitiligo Signature-Based Drug Screening Identifies Fulvestrant as a Novel Immunotherapy Combination Strategy
Oncology•
Machine Learning–Based Survival Prediction Tool for Adrenocortical Carcinoma
Oncology•
Dose reduction in 4D CT imaging: Breathing signal-guided deep learning-driven data acquisition
Oncology•
Development of a predictive model for distant metastasis in HCC patients post-TACE using clinical data, radiomics, and deep learning
Oncology•
Learning the cellular origins across cancers using single-cell chromatin landscapes
Oncology•
Potential of the World Health Organization's Skin NTDs App to Support and Improve the Detection of Skin-Related Neglected Tropical Diseases: Protocol for a Performance Evaluation and Feasibility Study in Senegal
Dermatology•
Web-based predictive tool for vaginal and vulvar melanomas: a machine learning study
Dermatology•
Identifying suspicious naevi with dermoscopy via variational autoencoder auxiliary generative classifiers
Dermatology•
Use of a Large Language Model as a Dermatology Case Narrator: Exploring the Dynamics of a Chatbot as an Educational Tool in Dermatology
Dermatology•
A Metabolism-Driven Prognostic Model and PSMD14-SP1-GYS1 Axis Reveal Therapeutic Vulnerabilities in Melanoma
Dermatology•
Patient Perceptions of Artificial Intelligence and Telemedicine in Dermatology: Narrative Review
Dermatology•
The unmet potential of patient context in melanoma AI: Addressing design and data biases
Dermatology•
Advancing equity in generative AI dermatology requires representative data and transparent evaluation
Dermatology•
Development and validation of a deep learning-based fully automated algorithm for pre-TAVR CT assessment of the aortic valvular complex and detection of anatomical risk factors: a retrospective, multicentre study
Cardiology/Cardiovascular Surgery•
AI-based detection and classification of anomalous aortic origin of coronary arteries using coronary CT angiography images
Cardiology/Cardiovascular Surgery•
Advancing Point-of-Care Still's Murmur Identification: Evaluating the Efficacy of ConvNets and Transformers Using the StethAid Multicenter Heart Sound Database
Pediatrics•
PET-Computed Tomography in the Management of Sarcoma by Interventional Oncology
Pediatrics•
New frontiers in radiologic interpretation: evaluating the effectiveness of large language models in pneumothorax diagnosis
Pediatrics•
An Adaptive Pragmatic Randomized Controlled Trial of Emergency Department Acupuncture for Acute Musculoskeletal Pain Management
Emergency Medicine•
Salbutamol for analgesia in renal colic: a prospective, randomized, placebo-controlled phase II trial
Emergency Medicine•
Comparison of ventilation modes in non-traumatic out-of-hospital cardiac arrest: SYMEVECA phase 2
Emergency Medicine•
PEAChY-O: Pharmacological Emergency Management of Agitation in Children and Young People: A Randomized Controlled Trial of Oral Medication
Emergency Medicine•
Laryngeal mask vs. laryngeal tube trial in paediatric patients (LaMaTuPe): a single-blinded, open-label, randomised-controlled trial
Emergency Medicine•
The Precision Resuscitation With Crystalloids in Sepsis (PRECISE) Trial: A Trial Protocol
Emergency Medicine•
The significance of possible non-occlusive mesenteric ischemia in relation to neurological outcomes in patients with refractory cardiac arrest – Secondary analysis of the Prague OHCA study
Emergency Medicine•
A Review of Physical Medicine and Rehabilitation Journals' Guidelines Regarding the Use of Artificial Intelligence in Manuscript Writing
PM&R•
Evaluating the utility of using ChatGPT 3.5 to generate research ideas for non-operative spine medicine.
PM&R•
Artificial intelligence in stroke rehabilitation: From acute care to long-term recovery
PM&R•
Systematic review of AI/ML applications in multi-domain robotic rehabilitation: trends, gaps, and future directions
PM&R•
ChatGPT in physiotherapy research and education: a boon or bane? - an overview
PM&R•
Current applications and outcomes of AI-driven adaptive learning systems in physical rehabilitation science education: A scoping review protocol
PM&R•
Machine learning-based prediction of post-operative outcomes in robotic-assisted radical prostatectomy: a multi-variable analysis of 758 cases
Urology•
Expert Evaluation of ChatGPT-4 Responses to Upper Tract Urothelial Carcinoma Questions: A Prospective Comparative Study with Guideline-Based and Patient-Focused Queries
Urology•
AI-informed computational pathology classifier predicts outcomes across treatment modalities in muscle-invasive urothelial carcinoma
Urology•
AI-driven preoperative risk assessment in kidney cancer surgery: A comparative feasibility study of machine learning models
Urology•
Latest Advancements and Future Directions in Prostate Cancer Surgery: Reducing Invasiveness and Expanding Indications
Urology•
Letter to the editor: interpretable machine learning model predicts 1‑year inguinal hernia risk after robot‑assisted radical prostatectomy
Urology•
Postoperative testicular metastasis in early to mid-stage gastric adenocarcinoma: a case report and literature review
Urology•
The Prognostic Value of a Validated and Automated Intravascular Ultrasound-Derived Calcium Score
Cardiology/Cardiovascular Surgery•
Artificial Intelligence–Based Fully Automated Quantitative Coronary Angiography vs Optical Coherence Tomography–Guided PCI: The FLASH Trial
Cardiology/Cardiovascular Surgery•
Optimizing CRT Lead Placement Accuracy With CMR-Guided On-Screen Targeting: A Randomized Controlled Trial (ADVISE-CRT III)
Cardiology/Cardiovascular Surgery•
Cardiac Rhythm Device Identification Using Neural Networks
Cardiology/Cardiovascular Surgery•
Utility of a Deep-Learning Algorithm to Guide Novices to Acquire Echocardiograms for Limited Diagnostic Use
Cardiology/Cardiovascular Surgery•
Comparing AI-Driven and Heart Team Decision-Making in Multivessel Coronary Artery Disease
Cardiology/Cardiovascular Surgery•
A fully automated artificial intelligence-driven software for planning of transcatheter aortic valve replacement
Cardiology/Cardiovascular Surgery•
Artificial Intelligence and Cardiovascular Genetics
Cardiology/Cardiovascular Surgery•
Enhanced Epileptic Seizure Detection Using CNNs with Convolutional Block Attention and Short-Term Memory Networks
Neurotechnology•
A systematic review of EEG-based machine learning classifications for obsessive-compulsive disorder: current status and future directions
Neurotechnology•
Salience Network Connectivity Predicts Response to Repetitive Transcranial Magnetic Stimulation in Smoking Cessation: A Preliminary Machine Learning Study
Neurotechnology•
How musicality enhances top-down and bottom-up selective attention: Insights from precise separation of simultaneous neural responses
Neurotechnology•
EEGOpt: A performance efficient Bayesian optimization framework for automated EEG signal classification
Neurotechnology•
Implantable Neural Speech Decoders: Recent Advances, Future Challenges
Neurotechnology•
AI-driven pupillary–computer interface via binary-coded flickering stimuli
Neurotechnology•
Efficient cognitive load decoding using causal spatiotemporal patterns from multimodal physiological signals
Neurotechnology•
MSAttNet: Multi-scale attention convolutional neural network for motor imagery classification
Neurotechnology•
Decoding binocular color differences via EEG signals: linking ERP dynamics to chromatic disparity in CIELAB space
Neurotechnology•
The interpretable deep learning framework and validation for seizure detection in pediatric electroencephalography: An improved accuracy and performance analysis
Neurotechnology•
Behavior Decoding Delineates Seizure Microfeatures and Associated Sudden Death Risks in Mouse Models of Epilepsy
Neurotechnology•
Technical Feasibility of Quantitative Susceptibility Mapping Radiomics for Predicting Deep Brain Stimulation Outcomes in Parkinson Disease
Neurotechnology•
Engineered Hydrogels as Functional Components in Controllable Neuromodulation for Translational Therapeutics
Neurotechnology•
Redefining insomnia: from neural dysregulation to personalized therapeutics
Neurotechnology•
Enhancing Automated Seizure Detection via Self-Calibrating Spatial-Temporal EEG Features with SC-LSTM
Neurotechnology•
MSAttNet: Multi-scale attention convolutional neural network for motor imagery classification
Neurotechnology•
From Electrophysiological to Biochemically-Modulated Interfaces: Evolution of Brain-Machine Communication
Neurotechnology•
Determining pediatric nurses’ anxiety levels, concerns, and metaphor perceptions towards artificial intelligence technologies: A mixed-method study
Pediatrics•
Automated Pediatric Delirium Recognition via Deep Learning-Powered Video Analysis
Pediatrics•
Comparative Evaluation of ChatGPT-4o and Grok-3 on Cleft Lip and Palate and Presurgical Infant Orthopedics: A Multidisciplinary Assessment by Orthodontists, Pediatricians, and Plastic Surgeons.
Pediatrics•
The Potential and Pitfalls of ChatGPT in Toxicological Emergencies
Pediatrics•
Illuminating radiogenomic signatures in pediatric‑type diffuse gliomas: insights into molecular, clinical, and imaging correlations. Part I: high‑grade group
Pediatrics•
Image-based drug screening combined with molecular profiling identifies signatures and drivers of therapy resistance in pediatric AML
Pediatrics•
Adaptive individualized gene pair signatures distinguishing melanoma and predicting response to immune checkpoint blockade
Dermatology•
Combining multi-omics analysis with machine learning to uncover novel molecular subtypes, prognostic markers, and insights into immunotherapy for melanoma
Dermatology•
Multi-Modal AI Integrating Dermoscopy, Histopathology, and Genomic Data for Precision Dermatology
Dermatology•
FairDITA: Disentangled Image-Text Alignment for Fair Skin Cancer Diagnosis
Dermatology•
Multi-Scale Attention Fusion With Depthwise Separable Convolutions for Efficient Skin Cancer Detection
Dermatology•
Non-invasive detection of choroidal melanoma via tear-derived protein corona on gold nanoparticles: a machine learning approach
Dermatology•
An artificial intelligence model of whole‑slide pathology specimens differentiating cutaneous high‑grade squamous proliferations
Dermatology•
Integrating pathology genomics and single-cell genomics to identify lactate metabolism-related prognostic features and therapeutic strategies for melanoma
Dermatology•
Challenges and Opportunities for AI in Dermatology Residency
Dermatology•
Evaluation of the Accuracy of Artificial Intelligence (AI) Models in Dermatological Diagnosis and Comparison With Dermatology Specialists
Dermatology•
https://www.jaadinternational.org/action/showPdf?pii=S2666-3287%2824%2900069-5
Dermatology•
Prognostication System For Squamos Cell Carcinoma Using Retrieval Augmented Generation-Enabled Large Language Model
Dermatology•
Predicting Future Severity of Atopic Dermatitis Using Flare Characteristics: A Cohort Study
Dermatology•
Development of Clinical Evaluation of an Artificial Intelligence Support Tool for Improving Telemedicine Photo Quality
Dermatology•
Consent and Identifiability for Patient Images in Research, Education, and Image-Based Artificial Intelligence
Dermatology•
Multi-task AI models in dermatology: Overcoming critical clinical translation challenges for enhanced skin lesion diagnosis
Dermatology•
Integration of a deep learning basal cell carcinoma detection and tumor mapping algorithm into the Mohs micrographic surgery workflow and effects of clinical staffing: A simulated, retrospective study
Dermatology•
Evaluating the appropriateness of skin cancer prevention recommendations obtained from an online chat-based artificial intelligence model
Dermatology•
Attention-Enhanced CNNs and transformers for accurate monkeypox and skin disease detection
Dermatology•
Artificial intelligence in ophthalmology: a bibliometric analysis of the 5-year trends in literature
Opthalmology•
Artificial intelligence in ophthalmology: a bibliometric analysis of the 5-year trends in literature
Opthalmology•
Application prospect of large language model represented by ChatGPT in ophthalmology
Opthalmology•
Advancing Question-Answering in Ophthalmology With Retrieval-Augmented Generation: Benchmarking Open-Source and Proprietary Large Language Models
Opthalmology•
AI-based assessment of Clinical Activity Score and detection of active thyroid eye disease using facial images: validation of Glandy CAS
Public Health•
Artificial-intelligence-driven governance: addressing emerging risks with a comprehensive risk-prevention-centred model for public health crisis management
Public Health•
Detection of pneumonia in children through chest radiographs using artificial intelligence in a low-resource setting: A pilot study
Public Health•
The incremental value of unstructured data via natural language processing in machine learning-based COVID-19 mortality prediction: a comparative study.
Public Health•
Developing an interpretable machine learning model for easily detecting insulin resistance among breast cancer survivors: a cross-sectional study
Public Health•
Development of a machine learning-based depression risk identification tool for older adults with asthma
Public Health•
InfEHR: Clinical phenotype resolution through deep geometric learning on electronic health records
Public Health•
Harnessing Geospatial Artificial Intelligence (GeoAI) for Environmental Epidemiology: A Narrative Review
Public Health•
Ratio of haemorrhagic area to retinal area as a novel indicator for AI-based screening of diabetic retinopathy in type 2 diabetes: a community-based cross-sectional study
Public Health•
Preferences of Patients With Tuberculosis for AI-Assisted Remote Health Management: Discrete Choice Experiment
Public Health•
Association between the changing trends of platelet distribution width and in-hospital mortality in critically ill patients with sepsis: a multicenter study based on machine learning
Public Health•
Artificial intelligence in the prescription of acute medical treatments in primary healthcare – comparison of the performance of family physicians and ChatGPT
Public Health•
Leveraging a Large Language Model for Streamlined Medical Record Generation: Implications for Healthcare Informatics
Public Health•
Artificial intelligence as a predictive tool for mental health status: Insights from a systematic review and meta-analysis
Public Health•
Evaluating the performance of ChatGPT in clinical multidisciplinary treatment: a retrospective study
Public Health•
Machine Learning Approach for Frailty Detection in Long-Term Care Using Accelerometer-Measured Gait and Daily Physical Activity: Model Development and Validation Study
Public Health•
Using Machine Learning Methods to Predict Early Treatment Outcomes for Multidrug-Resistant or Rifampicin-Resistant Tuberculosis to Enhance Patient Cure Rates: Development and Validation of Multiple Models
Public Health•
A machine learning-based fall-risk score for severity of fall-related adverse outcomes in community older adults
Public Health•
Using Large Language Models to Assess the Consistency of Randomized Controlled Trials on AI Interventions With CONSORT-AI: Cross-Sectional Survey
Public Health•
Large language model as clinical decision support system augments medication safety in 16 clinical specialties
Public Health•
Exploring Young Adults' Attitudes Toward AI-Driven mHealth Apps: Qualitative Study
Public Health•
The effect of the use of artificial intelligence in the preparation of patient education materials by nursing students on the understandability, actionability and quality of the material: A randomized controlled trial
Public Health•
Artificial intelligence-based computer aided detection (AI-CAD) in the fight against tuberculosis: Effects of moving health technologies in global health
Public Health•
Assisting the infection preventionist: Use of artificial intelligence for health care-associated infection surveillance
Public Health•
Human-Centric AI Governance: An Adaptive Public International Law Framework for Ethical and Inclusive AI Regulation in Public Health
Public Health•
TrialBench: Multi-Modal AI-Ready Datasets for Clinical Trial Prediction
Public Health•
Telehealth and Pharmacotherapy: The Role of Synchronous and Novel Asynchronous Digital Health Tools in Psychiatry
Psychiatry•
A case study of forensic psychiatry experts' reports analysis through large language models
Psychiatry•
The risk factors of obsessive-compulsive disorder: a cross-sectional study in Southwestern China
Psychiatry•
Leveraging social media and large language models for scalable alcohol risk assessment: Examining validity with AUDIT-C and post recency effects
Psychiatry•
Can Machine Learning predict therapeutic outcomes in affective and not affective psychosis? A systematic review and meta-analysis
Psychiatry•
Suicide and non-suicidal self-injury among Chinese adolescents: a longitudinal study based on the social ecological perspective
Psychiatry•
Bone marrow immune remodeling in depression: TNF/NF-\u03baB mediated leukocyte redistribution and construction of an interpretable predictive model.
Psychiatry•
Social Participation and Depressive Symptoms Among Older Adults.
Psychiatry•
Unraveling ADHD Through Eye-Tracking Procedures: A Scoping Review
Psychiatry•
Detecting suicide risk in bipolar disorder patients from lymphoblastoid cell lines genetic signatures
Psychiatry•
Integrated bulk and single-cell RNA sequencing identifies oxidative stress signatures of radiation-induced lung injury in mice through machine learning
Oncology•
Can polycythaemia vera disease be predicted from haematologic parameters? A machine learning-based study
Oncology•
Pathomics-based machine learning models for optimizing LungPro navigational bronchoscopy in peripheral lung lesion diagnosis
Oncology•
Nodal Spread Prediction in Human Oral Tongue Squamous Cell Carcinoma Using a Cancer-Testis Antigen Genes Signature
Oncology•
AI cancer driver mutation predictions are valid in real-world data
Oncology•
Large language model processing capabilities of ChatGPT 4.0 to generate molecular tumor board recommendations-a critical evaluation on real world data
Oncology•
An injury-associated lobular microniche is associated with the classical tumor cell phenotype in pancreatic cancer
Oncology•
CT-based radiomics deep learning signatures for noninvasive prediction of early recurrence after radical surgery in locally advanced colorectal cancer: A multicenter study
Oncology•
Identification of novel selective estrogen receptor degraders (SERD) via physics-based and deep-learning-based virtual screening and Bioassys
Oncology•
Preferences for adopting artificial intelligence in radiation therapy treatment: A discrete choice experiment
Oncology•
An injury-associated lobular microniche is associated with the classical tumor cell phenotype in pancreatic cancer
Oncology•
AI-driven MRI biomarker for triple-class HER2 expression classification in breast cancer: a large-scale multicenter study
Oncology•
Artificial intelligence applications in thyroid cancer care
Oncology•
Integrated multi-omics analysis reveals PTM networks as key regulators of colorectal cancer progression and immune evasion
Oncology•
ASO Author Reflections: Advancing Prognostics in Oncology: Developing a Machine Learning Model for Predicting 2-Year and 5-Year Survival Rates in Patients with Undifferentiated Pleomorphic Sarcoma.
Oncology•
Multimodal Integration of Liquid Biopsy and Radiology for the Noninvasive Diagnosis of Gallbladder Cancer and Benign Disorders
Oncology•
The Next Frontier in Pediatric Cardiology: Artificial Intelligence
Cardiology/Cardiovascular Surgery•
Predicting deterioration of ventricular function in patients with repaired tetralogy of Fallot using machine learning
Cardiology/Cardiovascular Surgery•
Evaluating the predictive potential of Th1 (IFN-γ+CD4+)/CD4+ in rapidly progressive amyotrophic lateral sclerosis
Neurology•
Epileptic seizure detection from electroencephalogram signals based on 1D CNN-LSTM deep learning model using discrete wavelet transform
Neurology•
Electroencephalography microstates as biomarkers for screening Alzheimer's disease: Feasibility analysis and a machine learning classification scheme
Neurology•
3D CoAt U SegNet-enhanced deep learning framework for accurate segmentation of acute ischemic stroke lesions from non-contrast CT scans
Neurology•
A Global-Local Dynamic Directed Graph Neural Network for Parkinson's Disease Detection
Neurology•
StrokeENDPredictor-19: Setting New Prediction Model in Neurological Prognosis in Acute Ischemic Stroke
Neurology•
Idea Density and Grammatical Complexity as Neurocognitive Markers
Neurology•
Association between estimation of pulse wave velocity and all-cause mortality in critically ill patients with ischemic stroke: a retrospective cohort study and predictive model establishment based on machine learning
Neurology•
Street view images help to reveal the impact of noisy environments on the survival duration of stroke patients
Neurology•
Artificial Intelligence for Ischemic Stroke Detection in Non-contrast CT: A Systematic Review and Meta-analysis
Neurology•
Leveraging multi-modal foundation model image encoders to enhance brain MRI-based headache classification
Neurology•
Prediction of personalized antiseizure medications response based on clinical signatures in epilepsy
Neurology•
Exploring transfer learning techniques for classifying Alzheimer's disease with rs-fMRI
Neurology•
Machine Learning Approaches to Racial/Ethnic Differences in Social Determinants of Mild Cognitive Impairment and Its Progression to Dementia in the All of Us Research Program
Neurology•
Clinical feasibility of motor hotspot localization based on electroencephalography using convolutional neural networks in stroke
Neurology•
Comparison of Two Auditory-Perceptual Evaluation Indexes, CAPE-V and GRBAS (Machine Learning), in Patients With Parkinson's Disease
Neurology•
Development and validation of a machine learning-based risk prediction model for post-stroke cognitive impairment
Neurology•
AI Devices in Neurology—Moving From Diagnosis to Prognosis
Neurology•
Construction of a novel online calculator for prediction of osteoporosis risk in Chinese type 2 diabetes patients
Orthopedics•
A Deep Learning Tool for Hip Minimum Joint Space Width Calculation on Antero-posterior Pelvis Radiographs
Orthopedics•
Open-Source AI for Vastus Lateralis and Adipose Tissue Segmentation to Assess Muscle Size and Quality
Orthopedics•
Fracture risk scores using output from an opportunistic screen of low bone density from conventional X-ray
Orthopedics•
Predicting periprosthetic joint Infection: Evaluating supervised machine learning models for clinical application
Orthopedics•
Artificial intelligence system for predicting areal bone mineral density from plain X-rays
Orthopedics•
Artificial Intelligence in Planning for Spine Surgery
Orthopedics•
Billing and Coding in Foot and Ankle Surgery; Can We Trust Artificial Intelligence?
Orthopedics•
Age and sex-related changes in proximal humeral volumetric BMD assessed via chest CT with a deep learning–based segmentation model
Orthopedics•
Development and evaluation of deep learning models for detecting and classifying various bone tumours in full-field limb radiographs using automated object detection models
Orthopedics•
ChatGPT-4o is Not a Reliable Study Source for Orthopedic Surgery Residents
Orthopedics•
Unlocking effective decision-making and critical thinking in orthopaedics: Insights from a narrative review
Orthopedics•
Machine Learning Predicts Mortality and Respiratory Failure in Patients Admitted With Rib Fractures
Orthopedics•
Can artificial intelligence in spine imaging affect current practice? Practical developments and their clinical status
Orthopedics•
Enhancing knee MRI bone marrow lesion detection with artificial intelligence: An external validation study
Orthopedics•
MobileTurkerNeXt: investigating the detection of Bankart and SLAP lesions using magnetic resonance images
Orthopedics•
Assessment and comparison of artificial intelligence–generated information regarding shoulder arthroplasty from multiple interfaces
Orthopedics•
Utilisation of AI-driven chatbots for perioperative health information seeking: a descriptive qualitative study of orthopaedic patients and family members
Orthopedics•
Automated quantitative analysis of peri-articular bone microarchitecture in HR-pQCT knee images
Orthopedics•
Rapid review: Growing usage of Multimodal Large Language Models in healthcare
Orthopedics•
Accelerated 3D qCEST of the Spine in a Porcine Model Using MR Multitasking at 3T
Orthopedics•
Evaluation of internal fixation stability of distal humerus C-type fractures based on musculoskeletal dynamics: finite element analysis under dynamic loading
Orthopedics•
Mechanisms and management of self-resolving lumbar disc herniation: bridging molecular pathways to non-surgical clinical success
Orthopedics•
AI-assisted 3D versus conventional 2D preoperative planning in total hip arthroplasty for Crowe type II-IV high hip dislocation: a two-year retrospective study.
Orthopedics•
Evaluation of a Large Language Model's Ability to Assist in an Orthopedic Hand Clinic
Orthopedics•
Multi-task learning for classification and prediction of adolescent idiopathic scoliosis based on fringe-projection three-dimensional imaging
Orthopedics•
Plasma endostatin and its association with new-onset acute kidney injury in critical care
Emergency Medicine•
Associations with early vomiting when using intranasal fentanyl and nitrous oxide for procedural sedation in children: A secondary analysis of a randomised controlled trial
Emergency Medicine•
Association between time to antibiotic and mortality in patients with suspected sepsis in the Emergency Department: post hoc analysis of the 1-BED randomized clinical trial
Emergency Medicine•
Factors in the Initial Resuscitation of Patients With Severe Trauma
Emergency Medicine•
Association of central capillary refill time with mortality in adult trauma patients: a secondary analysis of the crash-2 randomised controlled trial data
Emergency Medicine•
Comparison of the analgesic dose of intravenous ketamine versus ketorolac in patients with chest trauma: A randomized double-blind clinical trial
Emergency Medicine•
A predictive model for intracranial hemorrhage in adult patients receiving extracorporeal membrane oxygenation
Emergency Medicine•
Computational ethnography and public health: Scaling and deepening lived experience research on social determinants of health with large language models
Public Health•
A practical framework for appropriate implementation and review of artificial intelligence (FAIR-AI) in healthcare
Public Health•
Harnessing Artificial Intelligence and Digital Technology for Enhancing Routine Immunization Among Zero-Dose Children
Public Health•
Artificial Intelligence-Powered Detection Systems for Antibiotic Residues In Food and The Environment: A Mini Review With Special Focus on Milk Products and Environmental Matrices Analysis
Public Health•
Artificial intelligence guided dosing decisions: a qualitative study on health care provider perspectives
Public Health•
Development and evaluation of a machine learning prediction model for short-term mortality in patients with diabetes or hyperglycemia at emergency department admission
Public Health•
Machine Learning Algorithms for Adverse Drug Reactions Prediction and Identifying Its Determinants Among HIV Patients on Antiretroviral Therapy in the University of Gondar Comprehensive and Specialized Hospital, in Amhara Region, Ethiopia
Public Health•
Trustworthy AI in Telehealth: Navigating Challenges, Ethical Considerations, and Future Opportunities for Equitable Healthcare Delivery
Public Health•
A Trust-Aware Architecture for Personalized Digital Health: Integrating Blueprint Personas and Ontology-Based Reasoning
Public Health•
Predicting malnutrition in PLWHIV using machine learning in gondar, Ethiopia
Public Health•
Artificial Intelligence (AI)-assisted readout method for the evaluation of skin prick automated test results
Public Health•
Spatial heterogeneity and its influencing factors of cardiometabolic multimorbidity in a natural community population: a study based on Lingwu city, rural Northwest China
Public Health•
Simulating Empathic Interactions with Synthetic LLM-Generated Cancer Patient Personas
Public Health•
AI-Enabled, Text-Based Health Coaching and Navigation for Employees to Support Health Outcomes: Pre-Post Observational Study
Public Health•
Continuous Reaching and Grasping with a BCI Controlled Robotic Arm in Healthy and Stroke-Affected Individuals
Neurotechnology•
Engineered Hydrogels as Functional Components in Controllable Neuromodulation for Translational Therapeutics
Neurotechnology•
Continuous Reaching and Grasping With a BCI Controlled Robotic Arm in Healthy and Stroke-Affected Individuals
Neurotechnology•
Non-invasive brain technologies and their role in clinical applications
Neurotechnology•
Redefining Insomnia: From Neural Dysregulation to Personalized Therapeutics
Neurotechnology•
Optimized node-level capsule graph neural network for subject-independent emotion recognition from EEG signals
Neurotechnology•
EEGOpt: A performance efficient Bayesian optimization framework for automated EEG signal classification
Neurotechnology•
Efficient cognitive load decoding using causal spatiotemporal patterns from multimodal physiological signals
Neurotechnology•
The interpretable deep learning framework and validation for seizure detection in pediatric electroencephalography: An improved accuracy and performance analysis
Neurotechnology•
A systematic review of EEG-based machine learning classifications for obsessive-compulsive disorder: current status and future directions
Neurotechnology•
Toward Foundational Model for Sleep Analysis Using a Multimodal Hybrid-Self-Supervised Learning Framework
Neurotechnology•
Statistical characterization of cortical-thalamic dynamics evoked by cortical stimulation in mice
Neurotechnology•
Multi-source Discriminant Dynamic Domain Adaptation for Cross-subject Motor Imagery EEG Recognition
Neurotechnology•
Single-nucleus transcriptome atlas of orbitofrontal cortex in amyotrophic lateral sclerosis with a deep learning-based decoding of alternative polyadenylation mechanisms
Neurotechnology•
Technical Feasibility of Quantitative Susceptibility Mapping Radiomics for Predicting Deep Brain Stimulation Outcomes in Parkinson Disease
Neurotechnology•
Channelwise Regional Integrate and Multiple Firing Neuron: Improving the Spatiotemporal Learning of Spiking Neural Networks
Neurotechnology•
FourierMask: Explain EEG-based End-to-end Deep Learning Models in the Frequency Domain
Neurotechnology•
Machine learning based classification of imagined speech electroencephalogram data from the amplitude and phase spectrum of frequency domain EEG signal
Neurotechnology•
Bilingual comparison of the performance of GPT-4o and GPT-4 on ophthalmology residency examination questions – Analysis of responses in English and French
Opthalmology•
International consensuses and guidelines on diagnosing and managing cytomegalovirus (CMV) retinitis by the Asia-Pacific Vitreo-retina Society (APVRS), the Asia-Pacific Professors of Ophthalmology (AAPPO) and the Asia-Pacific Society of Ocular Inflammation and Infection (APSOII)
Opthalmology•
Large language models in ophthalmology: a scoping review on their utility for clinicians, researchers, patients, and educators
Opthalmology•
Real-world large sample evaluation of drug-related blepharoptosis: a pharmacovigilance analysis of the FDA Adverse Event Reporting System database
Opthalmology•
Global Trends and Emerging Themes in Tele-Ophthalmology Research: A Bibliometric Analysis (1993 to 2024)
Opthalmology•
Current status and solutions for AI ethics in ophthalmology: a bibliometric analysis
Opthalmology•
Ophthalmic drug discovery and development using artificial intelligence and digital health technologies
Opthalmology•
Computational Histology Artificial Intelligence (CHAI) Enhances Risk Stratification of High-grade Ta Nonmuscle-invasive Bladder Cancer in a Multicenter Cohort: Comparison to Current European Association of Urology and American Urological Association Stratification Schemes
Urology•
Role of artificial intelligence in predicting the renal function after nephrectomy in renal cell carcinoma: a systematic review and meta-analysis
Urology•
Evaluation of prostate cancer pathology reports generated by ChatGPT to enhance patient comprehension
Urology•
AI-assisted diagnosis of renal cell carcinoma: educational needs and cognitive assessment based on the WHO classification 2022
Urology•
Prognostic and Predictive value of Machine Learning-Based Biomarker and Pathomics Signatures in Patients with Prostate Cancer
Urology•
ChatGPT performance in answering medical residency questions in nephrology: a pilot study in Brazil
Urology•
Predicting postoperative fever in culture-negative patients undergoing mini-PCNL using MAP score-augmented machine learning: a retrospective cohort study
Urology•
Factors associated with admission to elderly medical-welfare facilities in South Korea: a cross-sectional machine-learning study
PM&R•
Advancing gait rehabilitation through wearable technologies: current landscape and future directions
PM&R•
Systematic review of AI/ML applications in multi-domain robotic rehabilitation: trends, gaps, and future directions
PM&R•
Research and application advances in rehabilitation assessment of stroke
PM&R•
Squat errors classification based on National Academy of Sports Medicine guidelines using IMU and deep learning algorithms
PM&R•
‘Human vs. Machine’ Validation of a Deep Learning Algorithm for Pediatric Middle Ear Infection Diagnosis
Pediatrics•
Machine Learning Insights Into Social Determinants Driving Child Abuse in Pediatric Traumatic Brain Injury
Pediatrics•
Artificial Intelligence-Based Analysis of Uroflowmetry Patterns in Children: A Machine Learning Perspective
Pediatrics•
Diagnostic and transition accuracy of natural language processing in high risk for psychosis individuals: A systematic review.
Psychiatry•
Using deep learning to predict internalizing problems from brain structure in youth
Psychiatry•
Understanding the countermovement to online presentations of psychiatric disorder that are perceived as "faked"
Psychiatry•
Performance of large language models ChatGPT and Gemini in child and adolescent psychiatry knowledge assessment
Psychiatry•
Heterogeneity in Effects of Automated Results Feedback After Online Depression Screening: Secondary Machine-Learning Based Analysis of the DISCOVER Trial
Psychiatry•
A systematic review of EEG-based machine learning classifications for obsessive-compulsive disorder: current status and future directions
Psychiatry•
Perplexity and proximity: Large language model perplexity complements semantic distance metrics for the detection of incoherent speech
Psychiatry•
Discovery of factors associated with smartphone addiction among high school adolescents: Using machine learning and network analysis
Psychiatry•
Artificial intelligence-driven closed-loop devices in sudden unexpected death in epilepsy prediction and prevention: Insights from persons with epilepsy and caregivers
Neurology•
rTMS modulates early AD progression via synergistic brain network reorganization and peripheral biomarker dynamics
Neurology•
Dynamic cheek surface modeling for enhanced hypomimia detection in Parkinson's disease
Neurology•
Blood Pressure Variability in Stroke: Building a Framework, Conceptualizing Intervention Opportunities, and Identifying Practical Research Objectives
Neurology•
Machine learning model for predicting the conversion to dementia using the Cube Copying Test
Neurology•
Deep Learning Modeling to Differentiate Multiple Sclerosis From MOG Antibody-Associated Disease
Neurology•
SpinalTRAQ: A Novel Pipeline for Volumetric Cervical Spinal Cord Analysis Identifies the Corticospinal Tract Synaptic Projectome in Healthy and Post-stroke Mice
Neurology•
Mendelian randomisation and singlecell transcriptomic analyses reveal serotonin promotes multiple sclerosis progression by suppressing adenosine deaminase activity
Neurology•
Large Language Models in Neurological Practice: Real-World Study
Neurology•
Characterization of SPTLC2 as a key driver promoting microglial activation and energy metabolism reprogramming after ischemic stroke through bulk and single-cell analyses combined with experimental validation
Neurology•
CQ-CNN: A lightweight hybrid classical-quantum convolutional neural network for Alzheimer's disease detection using 3D structural brain MRI
Neurology•
Can we trust AI for acne advice: A double-blind performance comparison with NICE guidelines
Dermatology•
Tumoral Skin Invasion Is an Independent Predictor of Rapid Recurrence in Head and Neck Cancer
Dermatology•
DNA methylation markers for oral cancer detection in non‑ and minimally invasive samples: a systematic review
Dermatology•
Advancing non-invasive melanoma diagnostics with deep learning and multispectral photoacoustic imaging
Dermatology•
Lightweight Unet with depthwise separable convolution for skin lesion segmentation
Dermatology•
Artificial Intelligence Measured Tumor Burden and Pre-Treatment Circulating Tumor DNA in Human Papilloma Virus-Associated Oropharynx Cancer
Dermatology•
Uncertainty-aware ensemble of foundation models differentiates glioblastoma from its mimics
Oncology•
Machine learning-based models for screening of anemia and leukemia using features of complete blood count reports
Oncology•
Early Prediction and Risk Analysis Using Hybrid Deep Learning Techniques in Biomedical Image Processing for Cancer Detection
Oncology•
Scrolling surgeons: Assessment of social media and artificial intelligence usage in gynecologic oncology fellows and fellowship programs
Oncology•
SAGERank: inductive learning of protein-protein interaction from antibody-antigen recognition
Oncology•
Accuracy of ChatGPT-4 Plus in Providing Information on Oral Cancer Management
Oncology•
A deep learning model for epidermal growth factor receptor prediction using ensemble residual convolutional neural network
Oncology•
Explainable prediction of hypothermia risk in laparoscopic surgery: a retrospective cross-sectional study using machine learning
Oncology•
Enhancing the identification of malonylation sites using AlphaFold2 and ensemble learning
Oncology•
Detecting pancreaticobiliary maljunction in pediatric congenital choledochal malformation patients using machine learning methods
Oncology•
Machine learning-based prediction of luminal breast cancer subtypes using polarised light microscopy
Oncology•
Screening for cardiac contractile dysfunction using an artificial intelligence–enabled electrocardiogram
Cardiology/Cardiovascular Surgery•
Accuracy of a deep learning-based algorithm for the detection of thoracic aortic calcifications in chest computed tomography and cardiovascular surgery planning
Cardiology/Cardiovascular Surgery•
Cardiac Microanatomy Imaging Using Forward-viewing Optical Coherence Tomography Endoscope
Cardiology/Cardiovascular Surgery•
An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction.
Cardiology/Cardiovascular Surgery•
Clinical validation of an AI-based blood testing device for diagnosis and prognosis of acute infection and sepsis
Emergency Medicine•
Comparative Efficacy of Face-to-Face and Right-Rear Upright Intubation in a Randomized Crossover Manikin Study
Emergency Medicine•
Effect of the score predicting imminent delivery on the management of unexpected out-of-hospital obstetrical deliveries: a cluster randomized clinical trial
Emergency Medicine•
Prior year hospital admission predicts 30-day hospital readmission after spine surgery
Orthopedics•
MRI detection and grading of knee osteoarthritis - a pilot study using an AI technique with a novel imaging-based scoring system
Orthopedics•
Use of artificial intelligence for classification of fractures around the elbow in adults according to the 2018 AO/OTA classification system
Orthopedics•
Comparative Evaluation of Deep Learning and Foundation Model Embeddings for Osteoarthritis Feature Classification in Knee Radiographs
Orthopedics•
Artificial intelligence and machine learning capabilities in the detection of acute scaphoid fracture: a critical review
Orthopedics•
Automatic detection of temporomandibular joint osteoarthritis radiographic features using deep learning artificial intelligence. A Diagnostic accuracy study
Orthopedics•
A 3D multi-task network for the automatic segmentation of CT images featuring hip osteoarthritis
Orthopedics•
Developing and validating machine learning models to predict acetabular cup size in total hip arthroplasty
Orthopedics•
Battle of the Bots: Solving Clinical Cases in Osteoarticular Infections With Large Language Models
Orthopedics•
Artificial intelligence-assisted detection of fractures on radiographs with BoneView: a systematic review
Orthopedics•
Genicular Artery Embolization in Knee Osteoarthritis: Bringing Imaging and Machine Learning Into the 21st Century
Orthopedics•
Evaluating Large Language Models and Retrieval-Augmented Generation Enhancement for Delivering Guideline-Adherent Nutrition Information for Cardiovascular Disease Prevention: Cross-Sectional Study
Public Health•
Principles and Practices of Community Engagement in AI for Population Health: Formative Qualitative Study of the AI for Diabetes Prediction and Prevention Project
Public Health•
Evolving Health Information–Seeking Behavior in the Context of Google AI Overviews, ChatGPT, and Alexa: Interview Study Using the Think-Aloud Protocol
Public Health•
Reinforcement Learning to Prevent Acute Care Events Among Medicaid Populations: Mixed Methods Study
Public Health•
The Role of Data in Public Health and Health Innovation: Perspectives on Social Determinants of Health, Community-Based Data Approaches, and AI
Public Health•
Integrating a knowledge-based artificial intelligence chatbot into nursing training programs: a comparative quasi-experimental study in Egypt and Saudi Arabia
Public Health•
Artificial intelligence-assisted ultrasound screening for breast cancer in China: a prospective, clustered, controlled, population-based study.
Public Health•
Hand, Foot, and Mouth Disease Risk Prediction in Southern China: Time Series Study Integrating Web-Based Search and Epidemiological Surveillance Data
Public Health•
Evaluation of Machine Learning Model Performance in Diabetic Foot Ulcer: Retrospective Cohort Study
Public Health•
The Digital Therapeutic Alliance With Mental Health Chatbots: Diary Study and Thematic Analysis
Public Health•
Invisible Bias in GPT-40-mini: Detecting Disparities in AI-Generated Patient Messaging
Public Health•
Predicting hematologic toxicity in advanced cervical cancer patients using interpretable machine learning models based on radiomics and dosimetrics
Public Health•
Real-World Evidence Synthesis of Digital Scribes Using Ambient Listening and Generative Artificial Intelligence for Clinician Documentation Workflows: Rapid Review
Public Health•
Performance of several large language models when answering common patient questions about type 1 diabetes in children: accuracy, comprehensibility and practicality
Public Health•
AI-driven abstract generating: evaluating LLMs with a tailored prompt under the PRISMA-A framework
Public Health•
ChatGPT-Based Chatbot for Help Quitting Smoking via Text Messaging: An Interventional Study
Public Health•
Machine learning reveals limited predictive value of clinical factors for asthma exacerbations
Public Health•
Machine learning-assisted screening of clinical features for predicting difficult-to-treat rheumatoid arthritis
Public Health•
Interpretable Artificial Intelligence to Predict Perioperative Risk Factors for Failure to Rescue after Coronary Artery Bypass Grafting
Cardiology/Cardiovascular Surgery•
Using artificial intelligence to predict post-operative outcomes in congenital heart surgeries: a systematic review
Cardiology/Cardiovascular Surgery•
Artificial intelligence-enabled electrocardiography and echocardiography to track preclinical progression of transthyretin amyloid cardiomyopathy
Cardiology/Cardiovascular Surgery•
Performance of an AI prediction tool for new-onset atrial fibrillation after coronary artery bypass grafting
Cardiology/Cardiovascular Surgery•
A Deep Learning Model to Identify Mitral Valve Prolapse From the Echocardiogram
Cardiology/Cardiovascular Surgery•
Machine Learning Prediction of Response to Cardiac Resynchronization Therapy: Improvement Versus Current Guidelines
Cardiology/Cardiovascular Surgery•
Introducing AI as members of script concordance test expert reference panel: A comparative analysis
Opthalmology•
Generative artificial intelligence in ophthalmology: a scoping review of current applications, opportunities, and challenges
Opthalmology•
Disentangling representations of retinal images with generative models
Opthalmology•
Artificial intelligence-generated informed patient consent in various ophthalmological procedures: A comparative study of correctness, completeness, readability, and real-word application between Deepseek and Chatgpt 4o.
Opthalmology•
Leveraging ChatGPT for Report Error Audit: An Accuracy-Driven and Cost-Efficient Solution for Ophthalmic Imaging Reports
Opthalmology•
AI-powered insights: Analyzing ChatGPT’s responses on myofascial pain syndrome
PM&R•
Geriatricians Leading Innovation: Collaborating to Enhance Care as We Age
PM&R•
Physical Activity Misinformation on Social Media: Systematic Review
PM&R•
Combining radiomics of X-rays with patient functional rating scales for predicting satisfaction after radial fracture fixation: a multimodal machine learning predictive model
PM&R•
Real-time biofeedback monitoring rehabilitation of distal radius fracture
PM&R•
Using Machine Learning with Wearable Devices to Advance Research and Patient Care Using Spinal Cord Injury as a Model
PM&R•
Histopathology-only Artificial Intelligence for Prostate Cancer: Towards Accessible Risk Stratification
Urology•
Artificial intelligence-based method for renal function automatic assessment of each kidney using plain computed tomography (CT) scans
Urology•
Pathologist-like explainable AI for interpretable Gleason grading in prostate cancer
Urology•
Frailty is Independently Associated with Stress Urinary Incontinence in Women: A SHAP-Enhanced Machine Learning Analysis
Urology•
Quality assessment of patient‑facing urologic telesurgery content using validated tools
Urology•
Integrating Heart Rate Variability Improves Machine Learning-based Prediction of Panic Disorder Symptom Severity
Psychiatry•
Balancing ethics and statistics: machine learning facilitates highly accurate classification of mice according to their trait anxiety with reduced sample sizes
Psychiatry•
Interpretable Machine Learning approach for predicting clinically significant suicide risk: A case study of patients with major depressive disorder in Greece.
Psychiatry•
Use of Mobile Sensing Data for Longitudinal Monitoring and Prediction of Depression Severity: Systematic Review
Psychiatry•
Detecting Eating Disorders From Social Media Content: What Has Been Done and Where Do We Go Next?
Psychiatry•
Self-AttentionNeXt: Exploring schizophrenic optical coherence tomography image detection investigations
Psychiatry•
Decoding chronic stress: From behavioral-molecular dynamics in mice to clinical implications of cortisol and IL-17 in depression severity.
Psychiatry•
Explainable AI for Depression Detection and Severity Classification From Activity Data: Development and Evaluation Study of an Interpretable Framework.
Psychiatry•
Revolutionizing cross professional collaboration outcomes in TBI: emerging trends in diagnostics, personalized medicine, technological innovations and neurorehabilitation.
Pediatrics•
A longitudinal dataset of tile and corresponding dermoscopic images with metadata for identifying skin cancers
Dermatology•
Machine learning developed a macrophage signature for predicting prognosis, immune infiltration, and immunotherapy features in head and neck squamous cell carcinoma
Dermatology•
Machine Learning to Predict Extranodal Extension in Head and Neck Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis
Dermatology•
Machine learning model to classify chronic leg wounds and identify pyoderma gangrenosum
Dermatology•
Bridging the dermatological divide: The ethical deployment of artificial intelligence in low-resource settings
Dermatology•
Transformer-assisted broad learning for hybrid intelligence based skin cancer segmentation
Dermatology•
Pathologist-like explainable AI for interpretable Gleason grading in prostate cancer
Oncology•
Identification and tissue-level validation of ferroptosis-related genes in small intestinal neuroendocrine neoplasms based on machine learning
Oncology•
OncoMark: a high-throughput neural multi-task learning framework for comprehensive cancer hallmark quantification
Oncology•
Serum multiomics prediction of prognosis and adverse reactions to concurrent chemoradiotherapy in patients with esophageal cancer
Oncology•
Development and validation of a leukemia prognostic model through single-cell RNA sequencing and machine learning approaches
Oncology•
Artificial intelligence for breast cancer prevention: the vision ahead
Oncology•
Segmenting beyond the imaging data: creation of anatomically valid edentulous mandibular geometries for surgical planning using artificial intelligence
Oncology•
Deep Learning Based Multiomics Model for Risk Stratification of Postoperative Distant Metastasis in Colorectal Cancer
Oncology•
The WT1 protein molecule drives the proliferation and metastasis of anaplastic thyroid carcinoma through the EMT process
Oncology•
Advanced deep learning-based brain tumor classification using a novel customized CNN and optimized residual network
Oncology•
AI-driven pupillary–computer interface via binary-coded flickering stimuli
Neurotechnology•
An open-access EEG dataset from indigenous African populations for schizophrenia research
Neurotechnology•
Neural responses in premature infants to repetition and alternation stimulations: A CNN-based analysis of EEG signals for temporal and spatial insights
Neurotechnology•
Neural evidence for attentional resource allocation to postural control using brain-body imaging
Neurotechnology•
Medical SAM-Clip Grafting for brain tumor segmentation
Neurotechnology•
Abnormal Brain Connectivity Patterns in Children with Global Developmental Delay Accompanied by Cognitive Impairment: A Resting-State EEG Study
Neurotechnology•
Augmenting Electroencephalogram Transformer for Steady-State Visually Evoked Potential-Based Brain–Computer Interfaces
Neurotechnology•
Creative experiences and brain clocks
Neurotechnology•
A unifying psycho-neuroendocrine-developmental model for the cortisol awakening response primes human cognition and emotion: 2025 Dirk Hellhammer award.
Neurotechnology•
Divergent Brain Network Activity in Asymptomatic C9orf72 and SOD1 Variant Carriers Compared With Established Amyotrophic Lateral Sclerosis
Neurotechnology•
AI and neurotechnology: Ethical challenges, human rights, and quality of healthcareInteligencia artificial y neurotecnologías: retos éticos, derechos humanos y calidad asistencial
Neurotechnology•
Enhanced brain tumour segmentation using a hybrid dual encoder-decoder model in federated learning
Neurotechnology•
Lactate Transport via Glial MCT1 and Neuronal MCT2 Is Not Required for Synchronized Synaptic Transmission in Hippocampal Slices Supplied With Glucose
Neurotechnology•
AI and Neurotechnology: Ethical Challenges, Human Rights, and Quality of Healthcare
Neurotechnology•
Multi-layer stratified oncology platform utilizing transcriptomics, prostate cancer organoids, and modeling of drug response
Urology•
Improving prototypical parts abstraction for case-based reasoning explanations designed for the kidney stone type recognition
Urology•
Would Uro_Chat, a Newly Developed Generative Artificial Intelligence Large Language Model, Have Successfully Passed the In-Service Assessment Questions of the European Board of Urology in 2022?
Urology•
Quality of patient information on interstitial cystitis from artificial intelligence chatbots
Urology•
Construction and application of machine learning models for predicting intradialytic hypotension
PM&R•
Prevention and health care intervention of common injuries in long-distance running for college teachers
PM&R•
Evaluating generalization of arm movement identification using machine learning: From structured to semi-structured environments
PM&R•
Machine learning for sudden cardiac death prediction among older adults using community-based electronic health records
Public Health•
Advancing healthcare analytics: a thematic review of machine learning, health informatics, and real-world data applications
Public Health•
Comparison of Japanese Mpox (Monkeypox) Health Education Materials and Texts Created by Artificial Intelligence: Cross-Sectional Quantitative Content Analysis
Public Health•
Identifying subjective life expectancy risk factors in physically active and inactive middle-aged and older adults using machine learning models
Public Health•
Designing Patient-Friendly Messages: Tutorial on Applying Human-Centered, Self-Determination Theory With AI Considerations
Public Health•
Leveraging machine learning to predict mosquito bed net utilization among women of reproductive age in sub-Saharan Africa
Public Health•
Prediction of suicidal ideation and depression in the general population with subthreshold insomnia using machine learning models
Public Health•
AI in Adipose Imaging: Revolutionizing Visceral Adipose Tissue, Ectopic Fat, and Cardiovascular Risk Assessment
Public Health•
Evaluation of an AI-Based Clinical Decision Support System for Perioperative Care of Older Patients: Ethical Analysis of Focus Groups With Older Adults
Public Health•
Stratifying cardiovascular benefits from GLP-1RA: a multisource analysis of patient-level CVOT and real-world data using AI-driven methods
Public Health•
Large Language Models for Automating Clinical Trial Criteria Conversion to Observational Medical Outcomes Partnership Common Data Model Queries: Validation and Evaluation Study
Public Health•
Implementation of a Digital Health Intervention (CHAMP) for Self-Monitoring of Hypertension: Protocol for 3 Interlinked Implementation Studies
Public Health•
Evaluating trustworthiness in AI-Based diabetic retinopathy screening: addressing transparency, consent, and privacy challenges
Public Health•
Cardiovascular disease prevention in China: challenges and opportunities in the artificial intelligence-enabled digital health era
Public Health•
A machine-learning method for predicting the 1-year risk of death in maintenance hemodialysis patients based on continuous compliance with dialysis quality indicators
Public Health•
Development and evaluation of neighborhood social risk indices for surgery using outcome-specific machine-learning models
Public Health•
Burden and risk factors of depression in seniors from 1990-2021: a multi-database study based on EMR mining methods.
Public Health•
Automated Esophageal Cancer Staging From Free-Text Radiology Reports: Large Language Model Evaluation Study
Public Health•
AI Virtual Human–Augmented Game-Based Teaching to Enhance Emotional Intelligence in Nursing Students
Public Health•
Artificial Intelligence and Cardiovascular Genetics
Cardiology/Cardiovascular Surgery•
Explainable artificial intelligence identifies and localizes left ventricular scar in hypertrophic cardiomyopathy using 12-Lead electrocardiogram
Cardiology/Cardiovascular Surgery•
Artificial intelligence-based quantitative coronary angiography of major vessels using deep learning
Cardiology/Cardiovascular Surgery•
Evaluating Large Language Models and Retrieval-Augmented Generation Enhancement for Delivering Guideline-Adherent Nutrition Information for Cardiovascular Disease Prevention: Cross-Sectional Study
Cardiology/Cardiovascular Surgery•
Non-invasive detection of cardiac allograft rejection among heart transplant recipients using an electrocardiogram based deep learning model
Cardiology/Cardiovascular Surgery•
Evaluation of DeepSeek-R1 for Ophthalmic Diagnosis and Reasoning: A Comparison with OpenAI o1 and o3
Opthalmology•
Disentangling representations of retinal images with generative models
Opthalmology•
Multimodal foundation model and benchmark for comprehensive retinal OCT image analysis
Opthalmology•
The growing presence of AI-generated content in ophthalmology: a retrospective bibliographic analysis
Opthalmology•
GQ-DNABERT reveals GQ proximal enhancer-promoter interactions associated with tissue-specific transcription
Oncology•
Accurate somatic small variant discovery for multiple sequencing technologies with DeepSomatic
Oncology•
Image-based DNA sequencing encoding for detecting low-mosaicism somatic mobile element insertions.
Oncology•
Development and validation of a nomogram combining PI-RADS v2.1 and clinical indicators for the diagnosis of prostate cancer in patients with PSA ≤ 20 ng/mL
Oncology•
MicroRNA expression profiling of white adipose tissue in the torpor response of the house mouse (Mus musculus)
Oncology•
AI-driven 3D CT imaging prediction model for improving preoperative detection of visceral pleural invasion in early-stage lung cancer
Oncology•
Integrated Early Life Factors and Depression: A Multi-Level Investigation of Brain Structural, Immunometabolic, and Genetic Mechanisms
Psychiatry•
Real-world safety profile of zuranolone for postpartum depression: A FAERS analysis Author links open overlay panel
Psychiatry•
Practical AI application in psychiatry: historical review and future directions
Psychiatry•
DeepGAM: An interpretable deep neural network using generalized additive model for depression diagnosis: Data from the heart and soul study
Psychiatry•
Dynamical pattern of successive bits to predict the outcomes of the SSRI and rTMS depression therapies using EEG signals
Psychiatry•
A novel non-contact screening tool based on Vibraimage technology for detecting depressive disorder in psychiatric outpatients: A diagnostic accuracy study.
Psychiatry•
Using Wearable Device and Machine Learning to Predict Mood Symptoms in Bipolar Disorder: Development and Usability Study
Psychiatry•
Discovering robust biomarkers of psychiatric disorders from resting-state functional MRI via graph neural networks: A systematic review
Psychiatry•
Personalising Antidepressant Treatment for Unipolar Depression Combining Individual Choices, Risks and big Data: The PETRUSHKA Tool
Psychiatry•
Multi-modal predictive modeling of schizophrenia severity: Leveraging liver function indicators and cognitive scores with random forest and SVM
Psychiatry•
Targeting mechanisms of change as a path to precision psychotherapy for community settings.
Psychiatry•
Molecular Biomarkers and Machine Learning in Oral Cancer: A Systematic Review and Meta-Analysis
Dermatology•
Privacy preserving skin cancer diagnosis through federated deep learning and explainable AI
Dermatology•
Quantitative analysis of chest CT with deep learning to assess the efficacy of tofacitinib in the treatment of anti-MDA5+ dermatomyositis
Dermatology•
Applications of artificial intelligence in emotion recognition in pediatrics health care: Scoping review
Pediatrics•
Performance of several large language models when answering common patient questions about type 1 diabetes in children: accuracy, comprehensibility and practicality
Pediatrics•
Effect of a generative artificial intelligence digital scribe on pediatric provider documentation time, cognitive burden, and burnout
Pediatrics•
Prior year hospital admission predicts 30-day hospital readmission after spine surgery
Orthopedics•
MRI detection and grading of knee osteoarthritis - a pilot study using an AI technique with a novel imaging-based scoring system
Orthopedics•
Use of artificial intelligence for classification of fractures around the elbow in adults according to the 2018 AO/OTA classification system
Orthopedics•
Comparative Evaluation of Deep Learning and Foundation Model Embeddings for Osteoarthritis Feature Classification in Knee Radiographs
Orthopedics•
Artificial intelligence and machine learning capabilities in the detection of acute scaphoid fracture: a critical review
Orthopedics•
Automatic detection of temporomandibular joint osteoarthritis radiographic features using deep learning artificial intelligence. A Diagnostic accuracy study
Orthopedics•
A 3D multi-task network for the automatic segmentation of CT images featuring hip osteoarthritis
Orthopedics•
Developing and validating machine learning models to predict acetabular cup size in total hip arthroplasty
Orthopedics•
Battle of the Bots: Solving Clinical Cases in Osteoarticular Infections With Large Language Models
Orthopedics•
Artificial intelligence-assisted detection of fractures on radiographs with BoneView: a systematic review
Orthopedics•
Genicular Artery Embolization in Knee Osteoarthritis: Bringing Imaging and Machine Learning Into the 21st Century
Orthopedics•
Comprehensive Evaluation of Facet Joints Osteoarthritis Radiological Features on Lumbar CT: A Multitask Deep Learning Approach
Orthopedics•
Development and validation of machine learning models for predicting the risk of refracture after percutaneous kyphoplasty in OVCF patients
Orthopedics•
Preoperatively predicting failure to achieve the minimum clinically important difference and substantial clinical benefit for total knee arthroplasty patients using machine learning
Orthopedics•
Using Machine Learning to Predict-Then-Optimize Elective Orthopedic Surgery Scheduling to Improve Operating Room Utilization: Retrospective Study
Orthopedics•
A fully-automated technique for cartilage morphometry in knees with severe radiographic osteoarthritis – Method development and validation
Orthopedics•
AI as teacher: effectiveness of an AI-based training module to improve trainee pediatric fracture detection
Orthopedics•
Comparison between coronal FLASH and sagittal double echo steady state MRI in detecting longitudinal cartilage thickness change by fully automated segmentation - Data from the FNIH biomarker cohort
Orthopedics•
Quantifying the Trajectory of Percutaneous Endoscopic Lumbar Discectomy in 3D Lumbar Models Based on Automated MR Image Segmentation
Orthopedics•
Magnetic Resonance-Based Artificial Intelligence-Supported Osteochondral Allograft Transplantation for Massive Osteochondral Defects of the Knee
Orthopedics•
Advancement of an automatic segmentation pipeline for metallic artifact removal in post-surgical ACL MRI
Orthopedics•
Classification of knee osteoarthritis severity using markerless motion capture and long short-term memory fully convolutional network
Orthopedics•
HSGDNet: Hybrid Synthetic-Data-Guided Deep Learning With NLS Refinement for Fast Multi-Component T1ρ Knee Mapping
Orthopedics•
MR-Transformer: A Vision Transformer-based Deep Learning Model for Total Knee Replacement Prediction Using MRI
Orthopedics•
Multiple large language models versus clinical guidelines for postmenopausal osteoporosis: a comparative study of ChatGPT-3.5, ChatGPT-4.0, ChatGPT-4o, Google Gemini, Google Gemini Advanced, and Microsoft Copilot
Orthopedics•
The knowledge distillation-assisted multimodal model for osteoporosis screening
Orthopedics•
An Appraisal of the Quality of Development and Reporting of Predictive Models in Spine Surgery
Orthopedics•
Ultra-fast single-sequence magnetic resonance imaging (MRI) for lower back pain: diagnostic performance of a deep learning T2-Dixon protocol
Orthopedics•
The value of a deep learning image reconstruction algorithm for assessing vertebral compression fractures using dual-energy computed tomography
Orthopedics•
The role of imaging parameters in the diagnosis of developmental dysplasia of the hip based on artificial intelligence: A perspective
Orthopedics•
Radiomics classification of fresh and old vertebral compression fractures: Impact of compression grade and morphology on diagnostic performance
Orthopedics•
Development of Artificial Intelligence-Assisted Lumbar and Femoral BMD Estimation System Using Anteroposterior Lumbar X-Ray Images.
Orthopedics•
Development and Validation of a Machine Learning-Based Online Prognostic Model for Cervical Spondylosis Patients After Anterior Cervical Discectomy and Fusion: A Multicenter Study
Orthopedics•
Random Forest of epidemiological models for Influenza forecasting
Public Health•
Grounded large language models for diagnostic prediction in real-world emergency department settings
Public Health•
Machine Learning Applications in Population and Public Health: Guidelines for Development, Testing, and Implementation
Public Health•
Artificial Intelligence (AI) Adoption, Policies, and Goals in Family Medicine: A Survey of Department Chairs
Public Health•
Forecasting tuberculosis through mechanistic learning of transmission dynamics: Insights from a case study in India.
Public Health•
Ethical sourcing in the context of health data supply chain management: a value sensitive design approach
Public Health•
Transforming Chinese cohort studies through artificial intelligence: a new era of population health research
Public Health•
Co-exposure to heat and noise on workers’ health: evidence from a large-scale cross-sectional surveillance study in China
Public Health•
The effects of adverse childhood experiences on pregnancy loss and mental health outcomes among rural Chinese women: A causal machine learning approach
Public Health•
Spatial and spatiotemporal machine learning models for COVID-19 dynamics: A review of methodology and reporting practices
Public Health•
Advancing healthcare allocation and prevention of disability: the role of disease-based predictive model for disability in aging adults
Public Health•
Mentorship in African health and clinical research: addressing barriers and building research capacity
Public Health•
Enhancing Evidence Synthesis Efficiency: Leveraging Large Language Models and Agentic Workflows for Optimized Literature Screening
Public Health•
Evaluating the Effectiveness of Digital Social Robots in Reducing Loneliness Among Community-Dwelling Older Adults in Japan: Randomized Controlled Trial and Qualitative Analysis
Public Health•
Prediction of incident atrial fibrillation using deep learning, clinical models, and polygenic scores
Cardiology/Cardiovascular Surgery•
Unsupervised phenotypic clustering of cardiac MRI data reveals distinct subgroups associated with outcomes in ischemic cardiomyopathy
Cardiology/Cardiovascular Surgery•
Cardiac amyloidosis detection from a single echocardiographic video clip: a novel artificial intelligence-based screening tool
Cardiology/Cardiovascular Surgery•
Effectiveness of Artificial Intelligence Models for Cardiovascular Disease Prediction: Network Meta-Analysis
Cardiology/Cardiovascular Surgery•
Leveraging artificial intelligence for the management of postoperative delirium following cardiac surgery
Cardiology/Cardiovascular Surgery•
Detecting mind wandering via EEG and facial video features
Neurotechnology•
https://imagizer.imageshack.com/img924/4427/PEmtHm.png
Neurotechnology•
Cortical modulation through robotic gait training with motor imagery brain-computer interface enhances bladder function in individuals with spinal cord injury
Neurotechnology•
EEG microstates, spectral analysis, and risk prediction in epilepsy comorbid with mild cognitive impairment: alteration in intrinsic brain activity
Neurotechnology•
A deep learning-enriched framework for analyzing brain functional connectivity
Neurotechnology•
A unifying psycho-neuroendocrine-developmental model for the cortisol awakening response primes human cognition and emotion: 2025 Dirk Hellhammer award
Neurotechnology•
Clinician perspectives on explainability in AI-driven closed-loop neurotechnology
Neurotechnology•
CISCA and CytoDArk0: A cell instance segmentation and classification method for histo(patho)logical image Analyses and a new, open, Nissl-stained dataset for brain cytoarchitecture studies
Neurotechnology•
A multi-level teacher assistant-based knowledge distillation framework with dynamic feedback for motor imagery EEG decoding
Neurotechnology•
Post-Stroke Fine Hand Motion Intention Recognition Based on sEMG Decomposition and Residual Spiking Neural Networks
Neurotechnology•
Analysis of the analgesic mechanism of TENS-WAA in colonoscopy using the EEG-fNIRS system: a study protocol for a randomised controlled trial
Neurotechnology•
Deep intelligence: a four-stage deep network for accurate brain tumor segmentation
Neurotechnology•
SensoryGAN: AI-driven design of low-toxicity dairy flavor alternatives with integrated neurosensory and cellular safety validation
Neurotechnology•
A machine learning approach for detection of claustrophobic brain activity in electroencephalography
Neurotechnology•
Maturation of Neuronal Activity in the Human Cortex Exhibits Robust Spatial Gradients across the Birth Transition
Neurotechnology•
MCI Detection From Odor-Evoked EEG Using a Multibranch Attention-Based Temporal–Spectral CNN
Neurotechnology•
EEG microstate-based static and dynamic brain functional network differences in autism spectrum disorder children and tDCS interventional modulation
Neurotechnology•
Research on parallel computing of the olfactory neural network based on multithreading
Neurotechnology•
Advanced Neuromonitoring Techniques for Medical and Neurological ICU Patients
Neurotechnology•
Edge AI-Brain–Computer Interfaces System: A Survey
Neurotechnology•
Symmetric projection attractor reconstruction: Transcutaneous auricular vagus nerve stimulation for visually induced motion sickness
Neurotechnology•
An ensemble classifier for emotion classification from EEG and GSR signals for autism detection
Neurotechnology•
Source-Free Domain Adaptation for SSVEP-based Brain-Computer Interfaces
Neurotechnology•
Applications of machine learning in deep brain stimulation for major depressive disorder: a systematic review and meta-analysis
Neurotechnology•
Neural oscillation mechanisms of repetitive subconcussive impacts: a network study of microstate-specific cross-frequency coupling
Neurotechnology•
Mobile EEG (DreamMachine) and AI in Education: Toward Smarter Classrooms and Better Mental Health
Neurotechnology•
An ensemble classifier for emotion classification from EEG and GSR signals for autism detection
Neurotechnology•
Histopathology-based Artificial Intelligence Algorithms for the Prediction of Prostate Cancer Metastasis After Radical Prostatectomy
Urology•
Application of Large Language Models in Automated Interpretation of Urodynamic Parameters
Urology•
Virtual screening and experimental validation of small-molecule compounds targeting AR in prostate cancer
Urology•
Artificial-Intelligence-based Surgical Phase Recognition in Robot-Assisted Radical Prostatectomy and Cross-Surgeon Validation
Urology•
Real-world evidence in localized and locally advanced prostate cancer: applying artificial intelligence to electronic health records
Urology•
Comparative efficacy of high vs. low-frequency rTMS in enhancing language recovery post-stroke aphasia: A retrospective study
PM&R•
The Role of Artificial Intelligence in Exercise-Based Cardiovascular Health Interventions: A Scoping Review
PM&R•
Prevalence and risk factors of suicidal ideation amongst unaccompanied young refugees: a machine learning approach
Psychiatry•
Obsessive–compulsive disorder detection using ensemble of scalp EEG-based convolutional neural network
Psychiatry•
Neurodevelopmental deviations in schizophrenia: Evidences from multimodal connectome-based brain ages
Psychiatry•
Clinical predictors of treatment resistant depression.
Psychiatry•
Development and evaluation of a machine learning prediction model for short-term mortality in patients with diabetes or hyperglycemia at emergency department admission
Emergency Medicine•
Rapid Acute Coronary Syndrome Evaluation Over One Hour With High-Sensitivity Cardiac Troponin I: A United States-Based Stepped-Wedge, Randomized Trial
Emergency Medicine•
Impact of antibiotic post-prescription authorization in resource-limited emergency rooms and acute care units during the COVID-19 pandemic
Emergency Medicine•
Serial 12-Lead ECG-Based Deep-Learning Model for Hospital Admission Prediction in Emergency Department Cardiac Presentations: Retrospective Cohort Study
Emergency Medicine•
Clinical characteristics associated with septic shock complicating hypothermia: a retrospective cohort study from the MIMIC-IV database
Emergency Medicine•
Clinical Pathway Revision Increases Amoxicillin Monotherapy and 5-Day Durations of Therapy for Pediatric Community-Acquired Pneumonia in the Emergency Department and Urgent Care: A Quality Improvement Initiative
Emergency Medicine•
Development and validation of a machine learning model for early prediction of intensive care unit acquired weakness
Emergency Medicine•
Development and external validation of an artificial intelligence model for predicting mortality and prolonged ICU stay in postoperative critically ill patients: a retrospective study
Emergency Medicine•
Association between antithrombotic medications and intracranial hemorrhage among older patients with mild traumatic brain injury: a multicenter cohort study
Emergency Medicine•
Reinforcement Learning to Prevent Acute Care Events Among Medicaid Populations: Mixed Methods Study
Emergency Medicine•
Derivation and Validation of Predictive Models for Early Pediatric Sepsis
Emergency Medicine•
Potential of deep learning in advancing electrocardiography arrhythmia diagnosis in emergency medicine
Emergency Medicine•
Early diagnosis model of mycosis fungoides and five inflammatory skin diseases based on a multimodal data-based convolutional neural network
Dermatology•
Advancing Pediatric Teledermatology: Trends, Barriers, and Innovations in Access and Equity (2020–2024)
Dermatology•
Predicting Postoperative Recurrence Using a Support Vector Machine for Patients With Esophageal Squamous Cell Carcinoma: Machine Learning Modeling Development and Validation Study
Dermatology•
In vivo reflectance confocal microscopy and keratinocyte skin cancer : Reflectance confocal microscopy and artificial intelligence
Dermatology•
Artificial Intelligence–Detected Tumor-Infiltrating Lymphocytes and Outcomes in Anti–PD-1–Based Treated Melanoma
Dermatology•
Melanoma RBPome identification reveals PDIA6 as an unconventional RNA-binding protein involved in metastasis
Dermatology•
Development of a Predictive Calculator for the Need for Abdominoperineal Resection after Chemoradiation Therapy in Anal Squamous Cell Carcinoma
Dermatology•
Enhanced early skin cancer detection through fusion of vision transformer and CNN features using hybrid attention of EViT-Dens169
Dermatology•
Machine learning developed a macrophage signature for predicting prognosis, immune infiltration, and immunotherapy features in head and neck squamous cell carcinoma
Dermatology•
Assessing the performance of artificial intelligence models in evaluating inflammatory skin disease severity: a systematic review and meta-analysis
Dermatology•
Berberine suppresses colorectal cancer progression by inducing ferroptosis-mediated energy metabolism disorders
Oncology•
Histopathology-based Artificial Intelligence Algorithms for the Prediction of Prostate Cancer Metastasis After Radical Prostatectomy
Oncology•
An exploratory study on predicting HER2-positive expression status of breast cancer using ultrasound radiomics combined with machine learning models
Oncology•
Development and validation of a video-based deep learning model for distinguishing epileptic seizures from non-epileptic events in a pediatric cohort
Pediatrics•
Derivation and Validation of Predictive Models for Early Pediatric Sepsis
Pediatrics•
Multimodal foundation model and benchmark for comprehensive retinal OCT image analysis
Opthalmology•
The growing presence of AI-generated content in ophthalmology: a retrospective bibliographic analysis
Opthalmology•
International consensuses and guidelines on rhegmatogenous retinal detachment (RRD) surgery by the Asia-Pacific Vitreo-retina Society (APVRS), the Academy of Asia-Pacific Professors of Ophthalmology (AAPPO) and the Academia Retina Internationalis (ARI)
Opthalmology•
Automated detection of pediatric congenital heart disease from phonocardiograms using deep and handcrafted feature fusion
Pediatrics•
Artificial Intelligence in Benign Prostatic Hyperplasia
Urology•
Large language model chatbots for patient education in kidney stones: a scoping review
Urology•
From conventional scores to explainable AI: a six-method comparative framework for failure prediction in percutaneous nephrolithotomy
Urology•
Artificial Intelligence in Population-Level Gastroenterology and Hepatology: A Comprehensive Review of Public Health Applications and Quantitative Impact
Public Health•
Trust transfer from medical AI to doctors and hospitals: Integrating digital, AI, and scientific literacy in a cross-sectional framework
Public Health•
Large Language Models for Automating Clinical Trial Criteria Conversion to Observational Medical Outcomes Partnership Common Data Model Queries: Validation and Evaluation Study
Public Health•
Machine learning-based integration of pericoronary adipose tissue and clinical risk factors for cardiovascular risk prediction in type 2 diabetes: a retrospective cohort study
Public Health•
Evaluating global epidemiology of type 2 diabetes mellitus among the working-age population: A 60-year study by interpretable machine learning framework
Public Health•
Transforming Chinese cohort studies through artificial intelligence: a new era of population health research
Public Health•
Reimagining patient-reported outcomes in the age of generative AI
Public Health•
Real-time and digital remote nutritional assessment framework with the use of smartphone-enabled facial morphometrics and machine learning— a proof of concept
Public Health•
Forecasting tuberculosis through mechanistic learning of transmission dynamics: Insights from a case study in India
Public Health•
Large Language Models for Automating Clinical Trial Criteria Conversion to Observational Medical Outcomes Partnership Common Data Model Queries: Validation and Evaluation Study
Public Health•
Mentorship in African health and clinical research: addressing barriers and building research capacity
Public Health•
Artificial Intelligence (AI) Adoption, Policies, and Goals in Family Medicine: A Survey of Department Chairs
Public Health•
Driver risk-level identification incorporating personality traits, demographic characteristics, and driving behaviors
Psychiatry•
Development of a Recommendation Engine to University Student Mental Health Support Aligned With Stepped Care: Longitudinal Cohort Study
Psychiatry•
Longitudinal machine learning prediction of non-suicidal self-injury among Chinese adolescents: A prospective multicenter Cohort study
Psychiatry•
Opioid misuse detection from cognitive and physiological data with temporal fusion deep learning.
Psychiatry•
Functional Near-Infrared Spectroscopy in Schizophrenia Research: Progress, Challenges, and Future Directions
Psychiatry•
Automated Depression Detection From Text and Audio: A Systematic Review.
Psychiatry•
An Anxiety Screening Framework Integrating Multimodal Data and Graph Node Correlation
Psychiatry•
Enhancing schizophrenia diagnosis efficiency with EEGNet: a simplified recognition model based on γ band features.
Psychiatry•
Unmet educational accommodation needs and mental health outcomes in adults with disabilities: A machine learning approach.
Psychiatry•
Development of a Neural Network to Predict Optimal IOP Reduction in Glaucoma Management
Opthalmology•
Sociotechnical influences on the adoption and use of AI-enabled clinical decision support systems in ophthalmology: a theory-based interview study
Opthalmology•
AI in Aesthetic/Cosmetic Dermatology: Current and Future
Dermatology•
Artificial Intelligence-Driven Skin Aging Simulation as Novel Skin Cancer Prevention
Dermatology•
Artificial Intelligence Predicts Fitzpatrick Skin Type, Pigmentation, Redness, and Wrinkle Severity From Color Photographs of the Face
Dermatology•
Deep Feature Learning for Sudden Cardiac Arrest Detection in Automated External Defibrillators
Cardiology/Cardiovascular Surgery•
Artificial Intelligence in Mitral Valve Analysis
Cardiology/Cardiovascular Surgery•
A multi-level teacher assistant-based knowledge distillation framework with dynamic feedback for motor imagery EEG decoding
Neurotechnology•
Prognostic Value of Electroencephalography in Critically Ill Adult Patients with Traumatic Brain Injury: A Systematic Review
Neurotechnology•
Radiomics, machine learning, and deep learning for hippocampal sclerosis identification: a systematic review and diagnostic meta-analysis
Neurotechnology•
What traditional neuropsychological assessment got wrong about mild traumatic brain injury. III: the added value of advanced neuroimaging
Neurotechnology•
Error-related potentials in EEG signals: feature-based detection for human-robot interaction
Neurotechnology•
A 192-Channel 1D CNN-Based Neural Feature Extractor in 65nm CMOS for Brain-Machine Interfaces
Neurotechnology•
Longitudinal EEG-based assessment of neuroplasticity and adaptive responses to transcranial focused ultrasound stimulation
Neurotechnology•
Robust Spatiotemporal Prototype Learning for Spiking Neural Networks
Neurotechnology•
Error-related potentials in EEG signals: feature-based detection for human-robot interaction
Neurotechnology•
TFDISNet: Temporal-frequency domain-invariant and domain-specific feature learning network for enhanced auditory attention decoding from EEG signals
Neurotechnology•
A Contrastive Learning-Enhanced Residual Network for Predicting Epileptic Seizures Using EEG Signals
Neurotechnology•
推动儿科神经系统疾病的人工智能技术应用与创新 [Promote the application and innovation of artificial intelligence in pediatric neurological diseases]
Neurotechnology•
Assessing the Nature of Human Brain-Derived Extracellular Vesicles on Synaptic Activity Via the Development of an Air-liquid Microfluidic Platform
Neurotechnology•
Experimental and computational study of 40 Hz low-field magnetic stimulation modulating neural activity and pathology in a mouse model of Alzheimer's disease
Neurotechnology•
Development and clinical assessment of a novel AI-based diagnostic model for Hirschsprung's disease
Pediatrics•
Establishment of a Diabetes-Tailored Data Intelligence Platform Enhances Clinical Care, Enables Risk-Based Monitoring, and Facilitates Population-Health-Based Approaches at a Pediatric Diabetes Network
Pediatrics•
Leveraging Large Language Models to Generate Multiple-Choice Questions for Ophthalmology Education
Opthalmology•
Enhanced performance in automated diabetic retinopathy diagnosis achieved through Voronoi diagrams and artificial intelligence
Opthalmology•
Role of the rostral anterior cingulate cortex in emotion processing in Treatment Resistant Depression
Psychiatry•
Artificial intelligence as a predictive tool for mental health status: Insights from a systematic review and meta-analysis
Psychiatry•
Reconfiguration of functional brain hierarchy in schizophrenia
Psychiatry•
Metacognition mediates the relationship between anxiety and smartphone addiction in university students
Psychiatry•
Predicting treatment-seeking status for alcohol use disorder using polygenic scores and machine learning in a deeply-phenotyped sample
Psychiatry•
Deep learning algorithms reveal genomic markers for anxiety disorder in a large cohort of children with down syndrome
Psychiatry•
Predicting Mental and Neurological Illnesses Based on Cerebellar Normative Features
Psychiatry•
A multi-stage large language model framework for extracting suicide-related social determinants of health.
Psychiatry•
Personalised modelling of routine variability and affective states
Psychiatry•
Health-economic evaluation of an AI-powered decision support system for anemia management in in-center hemodialysis patients
Public Health•
Token Probabilities to Mitigate Large Language Models Overconfidence in Answering Medical Questions: Quantitative Study
Public Health•
Mortality prediction for ICU patients with mental disorders using large language models ensemble and unstructured medical notes
Public Health•
Using Artificial Intelligence in Vector Control: A New Public Path for Public Health
Public Health•
Social Media Recruitment in Indigenous and Native American Populations: Challenges in the AI Age
Public Health•
Predictive modelling in times of public health emergencies: patients' non-transport decisions during the COVID-19 pandemic
Public Health•
Human-Centric AI Governance: An Adaptive Public International Law Framework for Ethical and Inclusive AI Regulation in Public Health
Public Health•
Nurses’ Intention to Integrate AI Into Their Practice: Survey Study in Canada
Public Health•
Using Machine Learning to Predict-Then-Optimize Elective Orthopedic Surgery Scheduling to Improve Operating Room Utilization: Retrospective Study
Public Health•
Effects of attractions and social attributes on peoples’ usage intention and media dependence towards chatbot: The mediating role of parasocial interaction and emotional support
Public Health•
Identifying Predictors of Cervical Cancer Screening Uptake in Sub-Saharan Africa Using Machine Learning: Cross-Sectional Study
Public Health•
Understanding and Addressing Challenges With Electronic Health Record Use in Gynecological Oncology: Cross-Sectional Survey of Multidisciplinary Professionals in the United Kingdom and Co-Design of an Integrated Informatics Platform to Support Clinical Decision-Making
Public Health•
Exploring Women’s Perceptions of Traditional Mammography and the Concept of AI-Driven Thermography to Improve the Breast Cancer Screening Journey: Mixed Methods Study
Public Health•
Dermatologist-like explainable AI enhances melanoma diagnosis accuracy: eyetracking study
Dermatology•
Machine-learning convergent melanocytic morphology despite noisy archival slides
Dermatology•
Deep Learning Algorithms in the Diagnosis of Basal Cell Carcinoma Using Dermatoscopy: Systematic Review and Meta-Analysis
Dermatology•
Assessing the performance of artificial intelligence models in evaluating inflammatory skin disease severity: a systematic review and meta-analysis
Dermatology•
A comprehensive study on skin cancer detection using artificial neural network (ANN) and convolutional neural network (CNN)
Dermatology•
AI-Driven Innovation in Skin Kinetics for Transdermal Drug Discovery: Overcoming Barriers and Enchancing Precision
Dermatology•
Identification of key predictors of acute GVHD in pediatric acute Leukemia using machine learning methods
Pediatrics•
Artificial intelligence-based chatbots improve the efficiency of course orientation among medical students: a cross-sectional study
Medical Informatics•
Utilizing Big Data and Artificial Intelligence to Improve the Learning Experience: A Systematic Overview.
Medical Informatics•
Web based AI-driven framework combining multi-modal data with CNN and LLM for Parkinson’s disease diagnosis
Medical Informatics•
Using a Coloring Activity to Identify Children’s Development of Visual–Motor Integration: An Application of Artificial Intelligence
PM&R•
A Parallel and Efficient Transformer Deep Learning Network for Continuous Estimation of Hand Kinematics from Electromyographic Signals
PM&R•
Digital Technology Integration in Home-Based Exercise: A Systematic Review of Research Evolution, Applications, and Impact Mechanisms
PM&R•
A Smartphone Platform for Remote Motor Fitness Assessment and AI-Generated Personalized Exercise Programs for Older Adults: Randomized Controlled Trial
PM&R•
Digital and AI-assisted multimodal supportive care, combining physical activity, nutrition, and pain management during chemotherapy for advanced pancreatic cancer patients: study protocol of the European multicenter randomized controlled trial of the RELEVIUM project
PM&R•
Machine Learning-Based Prediction of Quality of Life Improvement After Surgery for Spinal Metastases
PM&R•
GPT-4o in Nutrition for Inpatients Undergoing Post-Stroke Rehabilitation: Identifying Dietary Errors, Exploring Expert-AI Rationale Differences, and Structuring AI-Expert Collaboration
PM&R•
Evaluating an AI-VR escape room for disaster nursing education: A quasi-experimental study
OB-GYN•
Development and Validation of a Machine Learning–Based Clinical Model for Predicting Rupture in Ectopic Pregnancy: A Web-Based Nomogram Approach
OB-GYN•
Interpretable machine learning model for predicting MII oocyte retrieved following controlled ovarian stimulation: a retrospective cohort study of 24,976 IVF/ICSI cycles
OB-GYN•
Exploring Women's Perceptions of Traditional Mammography and the Concept of AI-Driven Thermography to Improve the Breast Cancer Screening Journey: Mixed Methods Study
OB-GYN•
MCBL-UNet: A Hybrid Mamba-CNN Boundary Enhanced Light-weight UNet for Placenta Ultrasound Image Segmentatio
OB-GYN•
The CT-based deep learning model outperforms traditional anatomical classification models in preoperatively predicting complications and risk grade in partial nephrectomy
Urology•
Artificial intelligence meets medical rarity: evaluating ChatGPT’s responses on post-orgasmic illness syndrome
Urology•
Artificial Intelligence Across the Prostate Cancer Pathway: Screening, Imaging, Pathology, and Biomarkers
Urology•
Agreement between artificial intelligence, experts, and the European Association of Urology Guidelines: insights from a study on the management of benign prostatic hyperplasia
Urology•
Recent advances in the management of male infertility
Urology•
Decade-long landscape of transrectal ultrasound (TRUS) in prostate cancer research: trends, collaborations, and emerging frontiers
Urology•
Evaluation of an artificial intelligence model based on multiparametric transrectal ultrasound for localizing clinically significant prostate cancer by simulation of targeted biopsies
Urology•
Meta-Analysis of the Performance of AI-Driven ECG Interpretation in the Diagnosis of Valvular Heart Diseases
Cardiology/Cardiovascular Surgery•
Clinical implementation of an AI-enabled ECG for hypertrophic cardiomyopathy detection
Cardiology/Cardiovascular Surgery•
Redefining β-blocker response in heart failure patients with sinus rhythm and atrial fibrillation: a machine learning cluster analysis
Cardiology/Cardiovascular Surgery•
Diagnostic Performance of Machine Learning Algorithms for Predicting Heart Failure in Diabetic Patients: A Systematic Review and Meta-Analysis
Cardiology/Cardiovascular Surgery•
Toward a Clinically Actionable, Electronic Health Record–Based Machine Learning Model to Forecast 90-Day Change in Hemoglobin A1c in Youth With Type 1 Diabetes: Feasibility and Model Development Study
Pediatrics•
Automated detection of pediatric congenital heart disease from phonocardiograms using deep and handcrafted feature fusion
Pediatrics•
Evaluation of image quality in pediatric portable chest radiographs using AI‐based noise reduction and edge enhancement
Pediatrics•
Randomized Trial of Self-Selected Music Intervention on Pain and Anxiety in Emergency Department Patients with Musculoskeletal Back Pain
Emergency Medicine•
Effectiveness and Safety of Pharmacologic Therapies for Migraine in the Emergency Department: A Systematic Review and Bayesian Network Meta-analysis
Emergency Medicine•
Systematic vitamin K antagonist reversal with prothrombin complex concentrate in patients with mild traumatic brain injury: randomized controlled trial
Emergency Medicine•
Early clinical evaluation of a machine-learning system for risk prediction of trauma-induced coagulopathy in the prehospital setting
Emergency Medicine•
Automated Filtering and Visualization of Patient-Centered Data from Electronic Health Records in Emergency Care: A Scoping Review
Emergency Medicine•
Walking Aids and Locomotion Training in the Emergency Department
Emergency Medicine•
A Physiotherapy-Led Emergency Department Guideline (PLEDGE) for Patients Presenting With Low Back Pain: Pre- and Post-Implementation Study
Emergency Medicine•
Emergency Department Visits for Medication‑Related Events With vs Without Pharmacist Intervention: The URGEIM Randomized Clinical Trial
Emergency Medicine•
Using Wearable Device and Machine Learning to Predict Mood Symptoms in Bipolar Disorder: Development and Usability Study
Public Health•
Using Machine Learning Methods to Predict Early Treatment Outcomes for Multidrug-Resistant or Rifampicin-Resistant Tuberculosis to Enhance Patient Cure Rates: Development and Validation of Multiple Models
Public Health•
Three-layered semantic framework for public health intelligence
Public Health•
Clinical phenotype resolution through deep geometric learning on electronic health records
Public Health•
Synthetic data generation method improves risk prediction model for early tumor recurrence after surgery in patients with pancreatic cancer
Public Health•
Fostering trust and interpretability: integrating explainable AI (XAI) with machine learning for enhanced disease prediction and decision transparency.
Public Health•
Machine Learning Approach for Frailty Detection in Long-Term Care Using Accelerometer-Measured Gait and Daily Physical Activity: Model Development and Validation Study
Public Health•
Machine learning approaches to racial/ethnic differences in social determinants of mild cognitive impairment and its progression to dementia in the All of Us Research Program
Public Health•
Association between estimation of pulse wave velocity and all-cause mortality in critically ill patients with ischemic stroke: a retrospective cohort study and predictive model establishment based on machine learning
Public Health•
Predicting Childhood Anaemia in Nigeria: A Machine Learning Approach to Uncover Key Risk Factors
Public Health•
Exploring Young Adults' Attitudes Toward AI-Driven mHealth Apps: Qualitative Study
Public Health•
Diagnostic and transition accuracy of natural language processing in high risk for psychosis individuals: A systematic review.
Psychiatry•
Voice of Mind, a Deep Learning Model for Depression and Anxiety Assessment From Acoustic and Lexical Vocal Biomarkers.
Psychiatry•
Natural lithium isotope variations in serum after lithium administration as a novel biomarker for differentiating schizophrenia and bipolar disorder
Psychiatry•
Cross-Platform Availability of Smartphone Sensors for Depression Indication Systems: Mixed-Methods Umbrella Review
Psychiatry•
Development of a machine learning-based depression risk identification tool for older adults with asthma
Psychiatry•
Construction of diagnostic model and identification of key genes of bipolar disorder based on GA-KPLS
Psychiatry•
Auto-Masked Audio Spectrogram Transformer for depression detection from speech
Psychiatry•
A Multimodal Depression Consultation Dataset of Speech and Text with HAMD-17 Assessments
Psychiatry•
Mood instability as a transdiagnostic predictor of cannabis use in attention-deficit/hyperactivity disorder and depression: A natural language processing analysis of electronic health records from 13,025 adolescents
Psychiatry•
Developing a Tool for Identifying Clinical Risk From Free-Text Clinical Records: Natural Language Processing Study
Psychiatry•
The Role of Artificial Intelligence in Diagnosis and Management of Cutaneous Infections
Dermatology•
P007 Comparative real-world performance of an artificial intelligence as a medical device and consultant teledermatologists in diagnosing benign skin lesion subtypes
Dermatology•
Diagnostic accuracy of artificial intelligence in the diagnosis of pemphigus and pemphigoid groups of disorders based on clinical images: A systematic review and meta-analysis
Dermatology•
A systematic review and meta-analysis of artificial intelligence versus clinicians for skin cancer diagnosis
Dermatology•
AI14 Artificial intelligence-driven digital applications and tools for atopic dermatitis: understanding the current landscape
Dermatology•
Challenges and Limitations of Multimodal Large Language Models in Interpreting Pediatric Panoramic Radiographs
Pediatrics•
Artificial intelligence-supported facial feature analysis in medical genetics
Pediatrics•
Artificial intelligence-based analysis of body composition predicts outcome in patients receiving long-term mechanical circulatory support
Cardiology/Cardiovascular Surgery•
Diagnostic accuracy of artificial intelligence in detecting left ventricular hypertrophy by electrocardiograph: a systematic review and meta-analysis
Cardiology/Cardiovascular Surgery•
Identification of key proteins and pathways in myocardial infarction using machine learning approaches
Cardiology/Cardiovascular Surgery•
Automation in tibial implant loosening detection using deep-learning segmentation
Orthopedics•
Machine learning outperforms deep learning in adhesive capsulitis diagnosis: a clinical-radiomics model bridging PD-T2 MRI and multimodal data fusion
Orthopedics•
Machine learning and quantitative computed tomography radiomics prediction of postoperative functional recovery in paraplegic dogs
Orthopedics•
Evaluating the Efficacy of Various Deep Learning Architectures for Automated Preprocessing and Identification of Impacted Maxillary Canines in Panoramic Radiographs
Orthopedics•
Deep learning and conventional hip MRI for the detection of labral and cartilage abnormalities using arthroscopy as standard of reference
Orthopedics•
A novel segmentation-based deep learning model for enhanced scaphoid fracture detection
Orthopedics•
Automatic joint inflammation estimation based on regression neural networks
Orthopedics•
The Duke University Cervical Spine MRI Segmentation Dataset (CSpineSeg)
Orthopedics•
Extracorporeal cardiopulmonary resuscitation in trauma patients: An analysis of the ELSO registry
Emergency Medicine•
The Cost-effectiveness of Mild Hypercapnia after Out-of-Hospital Cardiac Arrest: a Health Economic Evaluation alongside the TAME Study
Emergency Medicine•
The Prognostic Accuracy of Frailty and Vulnerability Screening for Older Adults in the Emergency Department: A Systematic Review and Meta-analysis
Emergency Medicine•
Effect of an Educational Intervention on Knowledge and Skills of Police Officers Towards Prehospital Care for Road Traffic Accident Victims in Southwestern Uganda
Emergency Medicine•
A radiomics-driven machine learning model for predicting bladder cancer prognosis identifies genes associated with radiomic features
Urology•
Mapping the Application Landscape of Artificial Intelligence in Prostate Cancer: a Global Bibliometric Analysis
Urology•
Machine learning-based screening of characteristic factors for urinary tract infection following ureteral stone surgery and construction and validation of risk prediction models
Urology•
What Is Required for AI to Improve the Assessment and Treatment of Patients With Lower Urinary Tract Dysfunction? ICI-RS 2025
Urology•
Artificial intelligence–driven kidney organ allocation: systematic review of clinical outcome prediction, ethical frameworks, and decision-making algorithms
Urology•
ASO Author Reflections: Advancing AI-Based Surgical Phase Recognition in Robot-Assisted Radical Prostatectomy
Urology•
Leveraging Artificial Intelligence and Personalized Rehabilitation to Improve Long-Term Outcomes in Geriatric Hip Fracture Patients After Arthroplasty
PM&R•
Multiscale SPD manifold learning for rehabilitation exercise evaluation
PM&R•
Unsupervised machine learning models reveal two distinct post‑operative physical activity profiles among joint arthroplasty patients: a United Kingdom biobank cohort study
PM&R•
Machine learning identifies exosome related gene signatures for early prediction of non-small cell lung cancer
Oncology•
CarD-T: An Automated Pipeline for the Nomination and Analysis of Potential Human Carcinogens
Oncology•
Deep Learning-based Motion-Compensated Reconstruction for Accelerating Four-Dimensional Magnetic Resonance Fingerprinting
Oncology•
Addressing data heterogeneity in distributed medical imaging with heterosync learning
Oncology•
Characterizing immune profiles in hepatocellular carcinoma patients benefiting from pembrolizumab and lenvatinib using machine learning
Oncology•
3D electron cloud descriptors for enhanced QSAR modeling of anti-colorectal cancer compounds
Oncology•
High-acceleration pancreatobiliary MRI with deep learning-based super-resolution reconstruction for evaluating presumed pancreatic intraductal papillary mucinous neoplasm
Oncology•
NHOC/NHOP as novel biomarkers for predicting lymph node metastasis in NSCLC using PET/CT radiomics and machine learning: a two-center retrospective study
Oncology•
Machine Learning-Based Prognostic Model for Gastric Cancer Using Integrated Multi-Omics Data
Oncology•
Subvisual imaging signals as biomarkers of impending lung metastasis: A multicenter pan-cancer study
Oncology•
Improving Machine Learning Classification Predictions through SHAP and Features Analysis Interpretation.
Oncology•
Leveraging Large Language Models to Generate Multiple-Choice Questions for Ophthalmology Education
Opthalmology•
Enhanced performance in automated diabetic retinopathy diagnosis achieved through Voronoi diagrams and artificial intelligence
Opthalmology•
AngioReport: dataset and baseline methods for fundus angiography report generation
Opthalmology•
Application of machine learning models for predicting depression among older adults with non-communicable diseases in India
Public Health•
Predictive model of sleep disorders in pregnant women using machine learning and SHAP analysis
Public Health•
Quantifying Epistemic Uncertainty in Predictions for Safer Health AI Performance Under Dataset Shifts
Public Health•
Machine Learning Algorithms for Adverse Drug Reactions Prediction and Identifying Its Determinants Among HIV Patients on Antiretroviral Therapy in the University of Gondar Comprehensive and Specialized Hospital, in Amhara Region, Ethiopia
Public Health•
Machine learning-assisted screening of clinical features for predicting difficult-to-treat rheumatoid arthritis
Public Health•
Study protocol for an open-label, single-arm, mixed methods feasibility study of the MWIQ AI-powered decision support tool for diabetes management in GP practices
Public Health•
AI12 Prospective, multicentre, real-world sensitivities of an artificial intelligence as a medical device assessment and teledermatologist assessment in appropriately managing melanoma, squamous cell carcinoma and rare skin cancers referred on the urgent suspected cancer pathway
Dermatology•
Artificial intelligence for skin lesion classification and diagnosis in dermatology: A narrative review
Dermatology•
Effective skin cancer classification by modified and optimized inception-ResNet-V2 model Journal: Scientific Reports (Nature Portfolio)
Dermatology•
Large-scale neural network correlates of response inhibition associated with antidepressant response in major depressive disorder.
Psychiatry•
Predicting treatment retention in medication for opioid use disorder: a machine learning approach using NLP and LLM-derived clinical features.
Psychiatry•
Feelings behind words: A systematic review on how effective IS NLP-based assessment for mental health diagnosis in human studies.
Psychiatry•
Speech and Language Markers as Longitudinal Predictors of Youth Mental Health: A Systematic Review
Psychiatry•
Identifying key risk factors for intentional self-harm, including suicide, among a cohort of people prescribed opioid agonist treatment: A predictive modelling study
Psychiatry•
Identifying prenatal risk factors of postpartum depression with machine learning
Psychiatry•
The secrets of medical students’ psychological resilience: a dual perspective of machine learning and path analysis
Psychiatry•
Machine learning to optimize use of natriuretic peptides in the diagnosis of acute heart failure
Cardiology/Cardiovascular Surgery•
Diagnostic Accuracy of AI Algorithms in Aortic Stenosis Screening: A Systematic Review and Meta-Analysis
Cardiology/Cardiovascular Surgery•
Enhancing prediction accuracy for muscle invasion in bladder cancer using a dual-energy CT-based interpretable model incorporating habitat radiomics and deep learning
Urology•
Automated Kidney Tumor Segmentation in CT Images Using Deep Learning: A Multi-Stage Approach
Urology•
AI-driven abstract generating: evaluating LLMs with a tailored prompt under the PRISMA-A framework
Public Health•
Unburdening Patients and Clinicians Through Automation and Artificial Intelligence: Informatics Strategies for Reducing Administrative Burden
Public Health•
Ischemic heart disease mortality due to fine particulate matter in Seoul between 2016 and 2020
Public Health•
Artificial Intelligence in Population-Level Gastroenterology and Hepatology: A Comprehensive Review of Public Health Applications and Quantitative Impact
Public Health•
Optimizing pediatric emergency triage in low-resource settings: evidence-based strategies, task-shifting, and technological innovations
Public Health•
High-Throughput Computing to Detect Harmful Drug-Drug Interactions in Older Adults: Protocol for a Population-Based Cohort Study
Public Health•
Social determinants of health and brain connectivity predict physical activity behavior change after new cardiovascular diagnosis
Public Health•
Cancer Diagnosis Categorization in Electronic Health Records Using Large Language Models and BioBERT
Public Health•
Testing regular expression searches and machine learning models to determine housing instability and low income status from primary care electronic medical record data in Toronto, Ontario
Public Health•
Regulating AI in Nursing and Healthcare: Ensuring Safety, Equity, and Accessibility in the Era of Federal Innovation Policy
Public Health•
Machine learning based prediction of low birth weight and its associated risk factors: Insights from the Bangladesh Demographic and Health Survey 2022
Public Health•
Early adherence to biofeedback training predicts long-term improvement in stroke patients: A machine learning approach
PM&R•
Randomized Trial of Self-Selected Music Intervention on Pain and Anxiety in Emergency Department Patients with Musculoskeletal Back Pain
Emergency Medicine•
Effectiveness and Safety of Pharmacologic Therapies for Migraine in the Emergency Department: A Systematic Review and Bayesian Network Meta-analysis
Emergency Medicine•
Capillary refill time as a bedside perfusion indicator: associations with vital signs and triage acuity in the emergency department: a cross-sectional study
Emergency Medicine•
Reverse shock index multiplied by Glasgow Coma Scale score as a predictor of urgent trauma care and mortality in isolated severe traumatic brain injury: a 10-year nationwide validation study
Emergency Medicine•
One-Year Mortality of Patients After Emergency Department Treatment for Nonfatal Opioid Overdose
Emergency Medicine•
Antacid Monotherapy Is More Effective in Relieving Epigastric Pain Than in Combination With Lidocaine: A Randomized Double-blind Clinical Trial
Emergency Medicine•
A randomized control trial comparing Falls Reduction for Elderly Emergency Department (FREED) interventions and usual care
Emergency Medicine•
A Randomized Trial of Intraarterial Treatment for Acute Ischemic Stroke
Emergency Medicine•
Feasibility of rapid low dose buprenorphine initiation in an emergency department observation unit
Emergency Medicine•
Automated Skin Disease Classification Using Fine-Tuned MobileNetV2 Implemented with TensorFlow and Keras
Dermatology•
AI15 The use of artificial intelligence as a medical device and teledermatology in the assessment of Merkel cell carcinoma: a National Health Service case series
Dermatology•
AI03 Steps towards safely deploying the world’s first autonomous artificial intelligence as a medical device for skin cancer into a National Health Service teledermatology pathway
Dermatology•
A Multimodal Vision Foundation Model of Clinical Dermatology
Dermatology•
Speech Emotion Recognition in Mental Health: Systematic Review of Voice-Based Applications
Psychiatry•
Discovering robust biomarkers of psychiatric disorders from resting-state functional MRI via graph neural networks: A systematic review
Psychiatry•
Severity Classification of Anxiety and Depression Using Generalized Anxiety Disorder Scale and Patient Health Questionnaire: National Cross-Sectional Study Applying Classification and Regression Tree Models
Psychiatry•
An open-access EEG dataset from indigenous African populations for schizophrenia research
Psychiatry•
A Whole-Brain Connectome-Wide Signature of Transdiagnostic Depression Severity Across Major Depressive Disorder and Posttraumatic Stress Disorder
Psychiatry•
Effect of an AI agent trained on a large language model (LLM) as an intervention for depression and anxiety symptoms in young adults: A 28-day randomized controlled trial.
Psychiatry•
Machine-learning versus traditional methods for prediction of all-cause mortality after transcatheter aortic valve implantation: a systematic review and meta-analysis
Cardiology/Cardiovascular Surgery•
Machine learning of electrophysiological signals for the prediction of ventricular arrhythmias: systematic review and examination of heterogeneity between studies
Cardiology/Cardiovascular Surgery•
Accuracy of deep learning in the differential diagnosis of coronary artery stenosis: a systematic review and meta-analysis
Cardiology/Cardiovascular Surgery•
Development and external validation of a machine learning-based predictive model for acute kidney injury in hospitalized children with idiopathic nephrotic syndrome
Pediatrics•
Assessing deep learning artificial intelligence support for detecting elbow fractures in the pediatric emergency department
Pediatrics•
Machine learning-based evaluation of risk factors for carbapenem-resistant Klebsiella pneumoniae dissemination in neonatal units
Pediatrics•
Using Generative AI to Co-Design Digital Mental Health Interventions With Adolescents in Rural South Africa: Qualitative Thematic Analysis of Participatory Workshops
Public Health•
COVID‐19 Persian Misinformation Detection on Instagram: A Comparative Analysis of Machine Learning and Deep Learning Methods
Public Health•
Evaluation of inflammatory markers in survival analysis of patients undergoing radical cystectomy using machine learning
Urology•
A clinically validated AI framework for kidney cancer detection and characterization.
Urology•
Machine learning model predicts clotting risk during CRRT in ESKD patients: a SHAP-interpretable approach
Urology•
Predicting depression risk with machine learning models: identifying familial, personal, and dietary determinants
Psychiatry•
Interpreting psychiatric digital phenotyping data with large language models: a preliminary analysis
Psychiatry•
Introducing e-Motions: a novel intraoperative test for social cognition mapping. Triple validation in normative, schizophrenia, and autism spectrum disorder populations.
Psychiatry•
Predictive Value of Machine Learning for the Risk of In-Hospital Death in Patients With Heart Failure: A Systematic Review and Meta-Analysis
Cardiology/Cardiovascular Surgery•
Automated triage of cancer-suspicious skin lesions with 3D total-body photography
Dermatology•
Comparative performance of deep learning models and non-dermatologists in diagnosing psoriasis, dermatophytosis, and eczema
Dermatology•
Establishing and validating a new metabolic marker-driven prognosis signature for cutaneous melanoma
Dermatology•
Leveraging Large Language Models to Generate Multiple-Choice Questions for Ophthalmology Education
Opthalmology•
Enhanced performance in automated diabetic retinopathy diagnosis achieved through Voronoi diagrams and artificial intelligence
Opthalmology•
AngioReport: dataset and baseline methods for fundus angiography report generation
Opthalmology•
ACXNet hybrid deep learning model for cross task mental workload estimation using EEG neural manifolds
Neurotechnology•
RISNet: A variable multi-modal image feature fusion adversarial neural network for generating specific dMRI images
Neurotechnology•
DEF-DSVM: A deep ensemble feature learning and deepSVM approach for multifaceted analysis and diagnosis of Alzheimer’s disease from EEG signals
Neurotechnology•
EEG-based motor execution classification of upper and lower extremeties using machine learning
Neurotechnology•
Sparse scanning encoding and neural network decoding for compressed photoacoustic microscopy
Neurotechnology•
A multimodal functional structure-based graph neural network for fatigue detection
Neurotechnology•
Hierarchical attention enhanced deep learning achieves high precision motor imagery classification in brain computer interfaces
Neurotechnology•
BiVM: Accurate Binarized Neural Network for Efficient Video Matting
Neurotechnology•
An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer’s disease
Neurotechnology•
Augmenting Electroencephalogram Transformer for Steady-State Visually Evoked Potential-Based Brain–Computer Interfaces
Neurotechnology•
DMAE-EEG: A Pretraining Framework for EEG Spatiotemporal Representation Learning
Neurotechnology•
Role of artificial intelligence in medical image analysis
Neurotechnology•
Large Language Models in Critical Care Medicine: Scoping Review
Neurotechnology•
Effects of Deep Brain Stimulation on Autonomic Symptoms in Parkinson's Disease: A Scoping Review
Neurotechnology•
Epilepsy surgery: From bench to the clinics
Neurotechnology•
Patient Experience With Rechargeable Deep Brain Stimulation Generators for Obsessive-Compulsive Disorder
Neurotechnology•
Neural mechanisms underlying the recovery of voluntary control of motoneurons after paralysis with spinal cord stimulation
Neurotechnology•
Neuromodulation for Epilepsy
Neurotechnology•
Decoding brain age predictions from sleep electroencephalography across infancy to adolescence
Neurotechnology•
Artificial intelligence for epilepsy decision support
Neurotechnology•
Neural decoding reliability: Breakthroughs and potential of brain–computer interfaces technologies in the treatment of neurological diseases
Neurotechnology•
A dual-branch neural network and attention mechanism for decoding EEG-based motor imagery
Neurotechnology•
EEG-SGENet: A lightweight convolutional network integrating SGE for motor imagery brain-computer interfaces
Neurotechnology•
Progress in the combined application of Brain-Computer Interface and non-invasive brain stimulation for post-stroke motor recovery
Neurotechnology•
Artificial Intelligence for Noninvasive Health Diagnostics
Neurotechnology•
Neuromodulation in Lennox-Gastaut Syndrome: Emerging Therapies and Future Directions
Neurotechnology•
Effects of Deep Brain Stimulation and Botulinum Toxin to Manage Pisa Syndrome in Parkinson's Disease
Neurotechnology•
Model-based deep learning with fully connected neural networks for accelerated magnetic resonance parameter mapping
Neurotechnology•
QTcNet: a deep learning model for direct heart rate corrected QT interval estimation
Neurotechnology•
Artificial Intelligence in Mental Health Services Under Illinois Public Act 104‐0054: Legal Boundaries and a Framework for Establishing Safe, Effective AI Tools
Public Health•
Promoting Responsible DeepSeek Deployment in Health Care: Scoping Review Comparing Grey and White Literature
Public Health•
From risk factors to predictive modelling: applying machine learning to childhood malaria surveillance in resource-limited settings
Public Health•
Autonomous AI Prescribing a Drug to Prevent Severe Acute Graft-versus-Host Disease in HLA-Haploidentical Transplants
Public Health•
Predictive Model for Managing the Clinical Risk of Emergency Department Patients: A Systematic Review
Public Health•
Artificial Intelligence Across the Obesity Continuum: From Mechanistic Insights to Global Precision Prevention and Therapy
Public Health•
The U.S. diabetes belt and factors explaining the excess risk: Multifactorial modeling and machine learning analysis
Public Health•
Navigating the AI Frontier in Toxicology: Trends, Trust, and Transformation
Public Health•
A fairness-aware machine learning framework for maternal health in Ghana: integrating explainability, bias mitigation, and causal inference for ethical AI deployment
Public Health•
Understanding and Addressing Challenges With Electronic Health Record Use in Gynecological Oncology: Cross-Sectional Survey of Multidisciplinary Professionals in the United Kingdom and Co-Design of an Integrated Informatics Platform to Support Clinical Decision-Making
Public Health•
Models and Metrics for Medical Education in Urology: Medical Student Education, Resident Education, and Future Directions
Urology•
Multi-omics and machine learning framework reveals ABCG2 as a therapeutic target of Eleven Flavored Shenqi Tablets in clear cell renal cell carcinoma
Urology•
Temporal trends and machine learning prediction of depressive symptoms among Chinese middle-aged and elderly individuals: a national cohort study
Psychiatry•
Distinct Alpha Connectivity Patterns During Response Inhibition in Alcohol Use Disorder
Psychiatry•
Machine learning-based prediction of suicide risk using adult attention-deficit/hyperactivity disorder symptoms and depression indicators: insights from a nationally representative south korean survey.
Psychiatry•
Identifying Predictors of Problematic Substance Use Among Youth Living with HIV in Uganda: A Machine Learning Approach
Psychiatry•
EASNet: Edge-aware Segmentation Network for Skin Lesion Segmentation with Boundary-aware and Frequency Attention Mechanisms
Dermatology•
Development and Validation of Artificial Intelligence-based Method for Diagnosis of Mitral Regurgitation from Chest Radiographs
Cardiology/Cardiovascular Surgery•
Deriving novel atrial fibrillation phenotypes using a tree-based artificial intelligence-enhanced electrocardiography approach
Cardiology/Cardiovascular Surgery•
A streamlined CMR-derived machine-learning model for estimating cardiovascular biological age: development and validation in the UK-Biobank and Multi-Ethnic Study of Atherosclerosis
Cardiology/Cardiovascular Surgery•
Predictive value of machine learning for in-hospital mortality risk in acute myocardial infarction: a systematic review and meta-analysis
Cardiology/Cardiovascular Surgery•
Neuroenhancement by repetitive transcranial magnetic stimulation (rTMS) on DLPFC in healthy adults
Neurotechnology•
Deep brain stimulation and magnetic resonance-guided focused ultrasound in Parkinsonism and related disorders: State-of-the-Art and future prospects
Neurotechnology•
Brain–Pupil Coupling Revealed Through Deep Learning of Intracranial Recordings
Neurotechnology•
Real-world clinical impact of three commercial AI algorithms on musculoskeletal radiography interpretation: A prospective crossover reader study
Orthopedics•
Enabling technology in adult spinal deformity
Orthopedics•
Automated instance segmentation and registration of spinal vertebrae from CT-Scans with an improved 3D U-net neural network and corner point registration.
Orthopedics•
Artificial Intelligence Algorithm Supporting the Diagnosis of Developmental Dysplasia of the Hip: Automated Ultrasound Image Segmentation
Orthopedics•
Detection, Classification, and Segmentation of Rib Fractures From CT Data Using Deep Learning Models: A Review of Literature and Pooled Analysis
Orthopedics•
Risk calculator for long-term survival prediction of spinal chordoma versus chondrosarcoma: a nationwide analysis
Orthopedics•
Artificial intelligence-based prediction model for surgical site infection in metastatic spinal disease: a multicenter development and validation study
Orthopedics•
Super-resolution deep learning reconstruction to evaluate lumbar spinal stenosis status on magnetic resonance myelography
Orthopedics•
Feasibility of fully automatic assessment of cervical canal stenosis using MRI via deep learning
Orthopedics•
Insights From Inputs: Enhancing Revision Total Joint Arthroplasty Resource Allocation With Machine Learning Prediction
Orthopedics•
Artificial intelligence (AI) in radiological paediatric fracture assessment: an updated systematic review
Orthopedics•
International external validation of the SORG machine learning algorithm for predicting sustained postoperative opioid prescription after anterior cervical discectomy and fusion using a Taiwanese cohort of 1,037 patients
Orthopedics•
Mechanobiology-guided machine learning models for predicting long bone fracture healing across diverse scenarios
Orthopedics•
Feasibility of fully automatic assessment of cervical canal stenosis using MRI via deep learning
Orthopedics•
AI-driven optimization of spinal implant design using parametric modelling
Orthopedics•
Machine learning integration of multi-modal radiomics and clinical factors predicts refracture risk after percutaneous kyphoplasty in postmenopausal women
Orthopedics•
Deep learning model trained using multi-energy computed tomography (CT) data shows better metal artifact reduction for lumbar CT imaging
Orthopedics•
Early diagnosis of knee osteoarthritis severity using vision transformer
Orthopedics•
Artificial Intelligence Algorithm Supporting the Diagnosis of Developmental Dysplasia of the Hip: Automated Ultrasound Image Segmentation
Orthopedics•
Real-world clinical impact of three commercial AI algorithms on musculoskeletal radiography interpretation: A prospective crossover reader study
Orthopedics•
Automated instance segmentation and registration of spinal vertebrae from CT-Scans with an improved 3D U-net neural network and corner point registration.
Orthopedics•
Impact of test set composition on AI performance in pediatric wrist fracture detection in X-rays
Orthopedics•
Diagnostic Accuracy of Artificial Intelligence for Detection of Rib Fracture on X-ray and Computed Tomography Imaging: A Systematic Review
Orthopedics•
Fusion of X-Ray Images and Clinical Data for a Multimodal Deep Learning Prediction Model of Osteoporosis: Algorithm Development and Validation Study
Orthopedics•
From risk factors to predictive modelling: applying machine learning to childhood malaria surveillance in resource-limited settings
Pediatrics•
Early Dengue Prediction in Bangladesh: A Comparative Study With Feature Analysis, Explainable Artificial Intelligence, and Model Optimization
Public Health•
Modern integrative prostate cancer diagnostics
Urology•
Sarcopenia measured by artificial intelligence as a predictor of overall survival in localized bladder cancer, a multicenter study
Urology•
AI-powered SPOT imaging for enhanced myocardial scar detection and quantification
Medical Informatics•
Deep learning-based detection of depression by fusing auditory, visual and textual clues
Medical Informatics•
Artificial intelligence for biopsies and imaging modalities in systemic autoimmune rheumatic diseases: An instructive narrative review
Medical Informatics•
Personalized Cancer-Specific Protein-Aptamer Corona for Orthogonal Multiplex Cancer Diagnosis
Oncology•
Development of a Machine Learning-Based Predictive Model for Anastomotic Leakage Following Gastric Cancer Surgery
Oncology•
A risk prediction model for cervical cancer in adults: A study based on the national health interview survey (NHIS) 2019-2023
Oncology•
IV3TM: Inception V3 enabled bidirectional long short-term memory network for brain tumor classification
Oncology•
Programmed cell death-related genes define distinct molecular subtypes and risk profiles in hepatocellular carcinoma
Oncology•
Ligand-receptor interaction profiling as a predictive biomarker for anti-PD-1 therapy response in melanoma
Oncology•
Identification and analysis of metabolic reprogramming-related genes in triple-negative breast cancer
Oncology•
A novel machine learning-based method to quantify the effect of transcranial direct current stimulation on opioid users
Psychiatry•
Predictive model of sleep disorders in pregnant women using machine learning and SHAP analysis
Psychiatry•
Distinct Alpha Connectivity Patterns During Response Inhibition in Alcohol Use Disorder
Psychiatry•
Analysis and development of risk prediction models for chronic opioid use after surgery: a cohort study using the nationwide database.
Psychiatry•
Peripheral innate immune signature links migraine and depression: Identification of PTX3 and HP as shared diagnostic biomarkers
Psychiatry•
Predicting depression risk with machine learning models: identifying familial, personal, and dietary determinants
Psychiatry•
60889 Image Generation of Common Dermatological Diagnoses by Artificial Intelligence; Evaluation of the Potential for Education and Training Purposes
Dermatology•
Interpreting Deep Learning-Based Predictions of BRAF V600E Mutation Using Diagnostic Whole Slide Images in Skin Cutaneous Melanoma
Dermatology•
Evaluating Artificial Intelligence Models in Dermatology: Comparative Analysis
Dermatology•
First Clinical Use of a Novel AI-Based Imaging Tool to Enhance CTO PCI Planning
Cardiology/Cardiovascular Surgery•
Artificial Intelligence in detection of acute coronary occlusion in NSTEMI patients
Cardiology/Cardiovascular Surgery•
Identifying Key Predictors of Smoking Cessation Success: Text-Based Feature Selection Using a Large Language Model
Public Health•
Artificial intelligence in NSCLC management for revolutionizing diagnosis, prognosis, and treatment optimization: A systematic review
Public Health•
Scalable Big Data Platform With End-to-End Traceability for Health Data Monitoring in Older Adults: Development and Performance Evaluation
Public Health•
Predicting molecular types of adult-type diffuse gliomas based on MRI reports with large language models
Medical Informatics•
Personalised medicine through AIenhanced integration of diagnostic imaging and radiation therapy
Medical Informatics•
Integrated assessment of total airway count and pneumonia volume on chest computed tomography as a prognostic biomarker for coronavirus disease
Medical Informatics•
Artificial intelligence-enhanced three-dimensional echocardiography reveals left atrial-ventricular coupling index as a novel prognostic marker in coronary artery disease
Cardiology/Cardiovascular Surgery•
Non-invasive hemoglobin estimation with outcome prediction via deep learning analysis of ECG-derived cardiac micro-dynamics
Cardiology/Cardiovascular Surgery•
Automated HFrEF Diagnosis Using an Optimized TimeSformer Model in Echocardiography
Cardiology/Cardiovascular Surgery•
Performance of machine learning algorithms in predicting the need for surgical fixation in pediatric craniomaxillofacial trauma
Pediatrics•
Association Study on Multi-Timepoint DNA Methylation Levels of Serotonin Transporter Gene and Adolescent Psychological-Behavioral Development
Pediatrics•
Educational aspects of artificial intelligence in oral and maxillofacial radiology: insights from a scoping review
Medical Informatics•
Agentic systems in radiology: Principles, opportunities, privacy risks, regulation, and sustainability concerns
Medical Informatics•
Explainable machine learning predicts overall survival in female bladder cancer patients after radical cystectomy
Urology•
Artificial intelligence-driven prostate cancer diagnosis: Enhancing accuracy and personalizing patient care
Urology•
Words matter: Stigmatizing language in medical records of individuals electing medication for opioid use disorder.
Psychiatry•
Integrating clinical anxiety scales with pre-trained language models for anxiety recognition on social media
Psychiatry•
Comorbid anxiety predicts lower odds of MDD improvement in a trial of smartphone-delivered interventions
Psychiatry•
Machine learning and SHAP values explain the association between social determinants of health and post-stroke depression
Psychiatry•
Applications of artificial intelligence in emotion recognition in pediatrics health care: Scoping review
Pediatrics•
Explainable AI for sign language recognition models: Integrating Grad-Cam LIME and Integrated Gradients
PM&R•
Development of a machine learning-based model for predicting the functional outcome of patients with proximal femur fractures
PM&R•
Evaluating multivariable prediction models for Parkinson’s disease prognosis: a scoping review protocol
Neurology•
Surface-Based Multi-axis Longitudinal Disentanglement Using Contrastive Learning for Alzheimer’s Disease
Neurology•
Digital Therapeutics for Alzheimer's and Parkinson's Diseases: Current Trends and Future Perspectives
Neurology•
A graph transformer-based foundation model for brain functional connectivity network
Neurology•
Supplementation of aged garlic extract attenuates age-associated memory impairment and cognitive decline: Involvement of molecular pathways in the cortex and hippocampus
Neurology•
Epilepsy therapy beyond neurons: Unveiling astrocytes as cellular targets
Neurology•
Exploring synergies: Advancing neuroscience with machine learning
Neurology•
Evaluating Repetitive Transcranial Magnetic Stimulation in Spinocerebellar Ataxia: A Meta-Analysis of Efficacy and Safety
Neurotechnology•
Adjuvant effects of vagus nerve stimulation on post- stroke rehabilitation: a systematic review and meta- analysis
Neurotechnology•
EEG-based detection of early functional brain changes in subjective cognitive decline: a prospective cohort study
Neurotechnology•
Hybrid BCI-based instruction set for dual robotic arm control using EEG and eye movement signals
Neurotechnology•
Remote electrical neuromodulation for reducing procedural pain in patients with chronic migraine receiving onabotulinumtoxinA injections: A randomized sham-controlled study
Neurotechnology•
Functional Connectivity to the Cerebellum and Resting-State Networks Predict Earlier Improvement of Dystonia Following Globus Pallidus Internus-Deep Brain Stimulation (GPi-DBS)
Neurotechnology•
Calibration-free sEMG intention recognition via self-supervised pretraining and adversarial domain alignment for upper-limb rehabilitation
Neurotechnology•
Outcomes of neurosurgery and otolaryngology team surgery for revision vagus nerve stimulation implantation surgery
Neurotechnology•
Effects of deep brain stimulation on non‑motor symptoms in Parkinson’s disease: insights from longitudinal studies using consistent evaluation scales
Neurotechnology•
Differential Effect of M1 and Cerebellar Repetitive Transcranial Magnetic Stimulation on Balance Performance in Stroke
Neurotechnology•
Approach to epilepsy: overview and update of diagnosis and management
Neurotechnology•
Patients’ views on the use of artificial intelligence in healthcare: Artificial Intelligence Survey Aachen (AISA)—a prospective survey
Medical Informatics•
Artificial intelligence in digital pathology diagnosis and analysis: technologies, challenges, and future prospects
Medical Informatics•
Transforming breast cancer care: the critical role of digital pathology and artificial intelligence in biomarker testing and risk stratification
Medical Informatics•
ZhongdaChat-ED: a medical large language model for personalized erectile dysfunction health consultation and professional clinical decision-making using retrieval-augmented generation
Urology•
Machine learning model integrating radiomics and clinical features for predicting postoperative bleeding after percutaneous nephrolithotomy
Urology•
Benchmarking Large Language Models Against Multidisciplinary Tumor Boards in Urological Oncology: Results from the Blinded, Prospective CONCORDIA Study
Urology•
Multifactor machine learning models for predicting urinary tract infections: a pilot study
Urology•
Transforming Pediatric Urology With Artificial Intelligence: A Narrative Review of Current Evidence and Practice
Urology•
Physical activity trends as predictors of postoperative complications in oncology patients: A machine learning approach
Urology•
The role of perfusion index in the evaluation of patients with cancer
Emergency Medicine•
Survey of the situation of the prehospital emergency medical services system in Iran
Emergency Medicine•
A retrospective evaluation of phenobarbital versus benzodiazepines for treatment of alcohol withdrawal in a regional Canadian emergency department
Emergency Medicine•
Transfer versus direct-visit patients in medically underserved emergency departments: a retrospective cohort study
Emergency Medicine•
Predicting triage levels in patients presenting with cardiac-related symptoms: a comparison of supervised machine learning methods
Emergency Medicine•
Cumulative Incidence of Stroke Disability and Mortality Following Emergency Department Discharge for Dizziness: A Cohort Study
Emergency Medicine•
Artificial intelligence versus human expertise: ECG-based detection of occlusive myocardial infarction after cardiac arrest
Emergency Medicine•
Identification of children at very low risk of clinically-important brain injuries after head trauma: a prospective cohort study
Emergency Medicine•
Tissue Plasminogen Activator for Acute Ischemic Stroke
Emergency Medicine•
Data-driven queueing modelling: a simulation case study of emergency department crowding
Emergency Medicine•
Perceptions and Attitudes of Emergency Physicians in Saudi Arabia Regarding Medical Use of Artificial Intelligence
Emergency Medicine•
Diagnostic performance of the Myocardial-Ischaemic-Injury index machine-learning algorithm in patients with an initial indeterminate troponin
Emergency Medicine•
Machine learning-based short-term forecasting of COVID-19 hospital admissions using routine hospital patient data
Emergency Medicine•
Proof-of-concept comparison of an artificial intelligence-based bone age assessment tool with Greulich-Pyle and Tanner-Whitehouse version 2 methods in a pediatric cohort
Pediatrics•
Diagnostic performance of four AI tools in pharmacology MCQs: Accuracy, sensitivity, and specificity
Public Health•
Enhancing Maternal Health Surveillance in the United States Through Natural Language Processing
Public Health•
Machine learning for the prediction of blood transfusion risk during or after mitral valve surgery: a multicenter retrospective cohort study
Public Health•
Artificial Intelligence-Enhanced Wearable Blood Pressure Monitoring in Resource-Limited Settings: A Co-Design of Sensors, Model, and Deployment
Public Health•
Impact of artificial intelligence on the availability, accessibility, acceptability and quality of ophthalmic disease screening services: a scoping review
Public Health•
Predicting plaque-gingivitis risk in schoolchildren using an interpretable machine learning model: a cross-sectional study
Public Health•
Artificial Intelligence: Promises and Perils for Employer-Sponsored Mental Health and Well-Being Initiatives
Public Health•
Gaussian process modelling of infectious diseases using the Greta software package and GPUs
Public Health•
Characterizing and Predicting Refractory Rumination in Obsessive Compulsive Disorder
Psychiatry•
Can Large Language Models Address Problem Gambling? Expert Insights from Gambling Treatment Professionals
Psychiatry•
Novel electroencephalographic biomarkers for the prediction of responders to an experimental glutamatergic agent in patients with schizophrenia
Psychiatry•
Abnormal functional network connectivity mediates the relationship between depressive symptoms and cognitive decline in late-onset depression
Psychiatry•
Affective Dimensions in Maternal Voice During Child Feeding in Mothers With and Without Eating Disorder History—Findings From a Machine Learning Analysis of Speech Data
Psychiatry•
Distinct electroencephalogram microstate in patients with methamphetamine use disorder and obsessive-compulsive disorder
Psychiatry•
Common Variable Immunodeficiency Disorder: A Decade of Insights from a Cohort of 150 Patients in India and the Use of Machine Learning Algorithms to Predict Severity
Pediatrics•
Artificial Intelligence Length-of-Stay Forecasting and Pediatric Surgical Capacity
Pediatrics•
eCAPRI: a novel tool combining clinical and imaging data for post-TAVI mortality prediction
Cardiology/Cardiovascular Surgery•
A deep learning methodology for fully-automated quantification of calcific burden in high-resolution intravascular ultrasound images
Cardiology/Cardiovascular Surgery•
Heart failure diagnosis and ejection fraction classification via feature fusion model using non-contact vital sign signals
Cardiology/Cardiovascular Surgery•
Development and implementation of explainable AI-based machine learning models for predicting hospital stay and treatment costs in cardiovascular patients
Cardiology/Cardiovascular Surgery•
Unlocking the potential of vitreous humor in biomarker discovery for Alzheimer's Disease and Alzheimer's Disease-Related Dementias
Neurology•
A deep-learning model for one-shot transcranial ultrasound simulation and phase aberration correction
Neurology•
Electrophysiology and Functional Magnetic Resonance Imaging of Cue Craving: Potential Biomarkers for Therapeutic Neuromodulation in Addiction
Neurology•
Mutual learning for joint disease detection and severity prediction reveals multimodal pathogenesis for neurodegenerative disorders
Neurology•
Quieting "Food Noise": How GLP-1s and Mindfulness Rewire the Default Mode Network (DMN) and Reward Circuits
Neurology•
Core-Periphery Principle Guided State Space Model for Functional Connectome Classification
Neurology•
Cortical Graph Neural Networks to Predict Dementia Risk Based on MRI‐Derived Cortical Surface Morphonology.
Neurology•
Detecting patterns of atrophy in cognitively impaired individuals using portable, low-field MRI
Neurology•
Evaluating Spanish Translations of Emergency Department Discharge Instructions by a Large Language Model: Tool Validation and Reliability Study
Public Health•
Developing an AI-Assisted Tool That Identifies Patients With Multimorbidity and Complex Polypharmacy to Improve the Process of Medication Reviews: Qualitative Interview and Focus Group Study
Public Health•
Adoption of Machine Learning in US Hospital Electronic Health Record Systems: Retrospective Observational Study
Public Health•
Utilization of AI Among Medical Students and Development of AI Education Platforms in Medical Institutions: Cross-Sectional Study
Public Health•
Applying Innovative Methods to Develop Health Education Text Messages in Cancer Survivorship
Public Health•
Evaluation of the INCISIVE Services in Cancer Imaging: A Feasibility Study
Urology•
Evaluation of AI for prostate cancer detection in biparametric-MRI screening population data
Urology•
Limitations of Large Language Models in Assisting PI-RADS Scoring on Prostate Biparametric MRI Text Reports
Urology•
Development and Validation of a Generative Artificial Intelligence-Based Pipeline for Automated Clinical Data Extraction From Electronic Health Records: Technical Implementation Study
Urology•
Genetic relationships between the gut microbiota and prostate cancer: Mendelian randomization combined with bioinformatics analysis
Urology•
Deciphering lactate/lactylation networks in AML: integrated scRNA-seq and transcriptomics reveal functions and prognostic model
Oncology•
MicroRNAs in oncology: a translational perspective in the era of AI
Oncology•
Lymph Node Metastasis-Associated Spatiotemporal Mapping of the TFF3-Linked Niche in Breast Cancer: Integrating Radiogenomic Signatures with Immune-Ecosystem Remodeling
Oncology•
Co-mapping clonal and transcriptional heterogeneity in somatic evolution via GoT-Multi
Oncology•
A context-augmented large language model for accurate precision oncology medicine recommendations
Oncology•
Live imaging of skin immunity using two-photon microscopy: a short review
Dermatology•
Advancing skin cancer detection through deep learning and fusion of patient metadata and skin lesion images
Dermatology•
Diagnostic performance of convolutional neural network-based AI in detecting oral squamous cell carcinoma: a meta-analysis
Dermatology•
Cutting-edge AI technologies in skin cancer applications
Dermatology•
DermNet: integrative CNN-ViT architecture for bias mitigation in dermatological diagnostics using advanced unsupervised lesion segmentation
Dermatology•
Zebra bodies recognition by artificial intelligence (ZEBRA): a computational tool for Fabry nephropathy
Medical Informatics•
Multiomics Profiling of T-cell Leukemia and Lymphoma Enables Targeted Therapeutic Discovery
Medical Informatics•
ECG-based deep learning for chronic kidney disease detection and cardiovascular risk prediction
Cardiology/Cardiovascular Surgery•
AI in Patient Care: Evaluating Large Language Model Performance Against Evidence-Based Guidelines for Pulmonary Embolism
Cardiology/Cardiovascular Surgery•
Predicting functional results of percutaneous coronary intervention using machine learning modelling
Cardiology/Cardiovascular Surgery•
Electrocardiogram-based deep learning improves outcome prediction following cardiac resynchronization therapy
Cardiology/Cardiovascular Surgery•
Predicting the longitudinal efficacy of medication for depression using electroencephalography and machine learning.
Psychiatry•
Applying Machine Learning to Predict Complex Clinical Course in Youth With Eating Disorders
Psychiatry•
Students’ perceptions of AI mental health chatbots: an exploratory qualitative study at Sultan Qaboos University
Psychiatry•
Speech Emotion Recognition in Mental Health: Systematic Review of Voice-Based Applications.
Psychiatry•
Genotype-by-sex interaction analyses for alcohol use disorder across biobanks
Psychiatry•
From waterways to the brain: Unraveling the environmental triggers of depression through PPCPs-gene network convergence
Psychiatry•
Diagnosis of adolescent depression with sleep disorder based on network topological attributes and functional connectivity
Psychiatry•
The Efficacy of Rule-based Versus LLM-based Chatbots in Alleviating Symptoms of Depression and Anxiety: A Systematic Review and Meta-Analysis.
Psychiatry•
Developing a multivariable deep learning model to predict psychiatric illness in patients with epilepsy
Psychiatry•
Evaluating the Agreement Between ChatGPT-4 and Validated Mental Health Scales in Older Adults: A Cross-Sectional Study
Psychiatry•
From Social to Symbolic: Investigating the Neural Networks Involved in Emoji and Facial Expression Recognition
Neurology•
ADHD Classification with GCN via Joint Feature Learning among Nodes and Edges
Neurology•
Association between cognitive status and structural brain changes in Alzheimer’s disease: Clinical implication of lightweight deep learning-aided diagnosis
Neurology•
Explainable End-to-End Seizure Prediction via Stationary Wavelet Transform-Driven Dynamic Multiscale Fuzzy Clustering
Neurology•
Circulating inflammatory proteins predict dementia risk, are linked to structural brain changes and modifiable risk factors.
Neurology•
A preregistered, Open Pipeline for Early Cerebral Palsy Risk Assessment from Infant Videos
Neurology•
Multimodal diagnosis of Parkinson's disease with an internet-based collaborative agent architecture of medical language models.
Neurology•
The use of fully immersive virtual reality for screening neurodegenerative diseases: A systematic review of behavioral and diagnostic outcomes.
Neurology•
Predicting Alzheimer's Disease Assessment Scale from T1‐weighted MRIs by Fine‐tuning a Pretrained Deep Learning Model
Neurology•
Machine Learning-Integrated Explainable Artificial Intelligence Approach for Predicting Steroid Resistance in Pediatric Nephrotic Syndrome: A Metabolomic Biomarker Discovery Study
Pediatrics•
Machine learning-based time-to-event survival analysis in pediatric patients with severe sepsis
Pediatrics•
Exploring artificial intelligence literacy’s role in healthy behaviors and mental health
Public Health•
AI-driven speech biomarkers for disease diagnosis and monitoring: a systematic review and meta-analysis
Public Health•
Ambient Air Pollution, Greenness and Frailty in an Elder Asian Population: A Multi-Center Study with Long-Term Exposure
Public Health•
An artificial intelligence-powered learning health system to improve sepsis detection and quality of care: a before-and-after study
Public Health•
What Drives Microplastic Exposure in Human Blood and Feces? Machine Learning Reveals Potential Key Influencing Factors
Public Health•
Developing a Quality Evaluation Index System for Health Conversational Artificial Intelligence: Mixed Methods Study
Public Health•
Digital maternity care in Germany: a cross-sectional web-based survey on midwives’ perceptions
Public Health•
Bridging Global Disparities in Drug Allergy Through AI-Assisted Training for Non-Specialists: Findings From the Multinational ADAPT-2 Course
Public Health•
Prediction of renal cell carcinoma: Development and validation of machine learning model
Urology•
A multimodal vision–language model for generalizable annotation-free pathology localization
Urology•
Radiomics and Image-based Artificial Intelligence for Predicting Recurrence and Survival After Surgery in Localized Renal Cell Carcinoma: An APPRAISE-AI Systematic Review and Meta-analysis Author links open overlay panel
Urology•
Machine learning models in predicting viability after testicular torsion: a proof of concept study
Urology•
Multimodal AI generates virtual population for tumor microenvironment modeling
Oncology•
Predicting the Efficacy of Breast Cancer Neoadjuvant Chemotherapy Using Ultrasonography and Machine Learning
Oncology•
A combinatorial transcription factor screening platform for immune cell reprogramming
Oncology•
The Knowledge Connector decision support system for multiomics-based precision oncology
Oncology•
Artificial intelligence analysis of minimally invasive surgery data
Medical Informatics•
An artificial intelligence-powered learning health system to improve sepsis detection and quality of care: a before-and-after study
Medical Informatics•
A novel potential biomarker panel to diagnose depression derived from big proteomic data
Psychiatry•
Evaluating the impact of data biases on algorithmic fairness and clinical utility of machine learning models for prolonged opioid use prediction
Psychiatry•
Personalised machine-learning decision support for suicidal thoughts and behaviours in the psychiatric emergency department
Psychiatry•
Predicting Remission in Schizophrenia Using Machine Learning - Assessing the Impact of Sample Size and Predictor Overinclusion
Psychiatry•
Study on subtyping and Traditional Chinese Medicine treatment of depression based on machine learning and text mining
Psychiatry•
Moving beyond word error rate to evaluate automatic speech recognition in clinical samples: Lessons from research into schizophrenia-spectrum disorders
Psychiatry•
Evaluating the Feasibility and Acceptability of a Mobile Mental Health Intervention for Adolescent Depression and Anxiety
Psychiatry•
Deep learning predicts cardiac output from seismocardiographic signals in heart failure
Cardiology/Cardiovascular Surgery•
Development of an artificial intelligence-based algorithm for the detection of left atrial enlargement from feline thoracic radiographs
Cardiology/Cardiovascular Surgery•
Predictors of Paravalvular Leakage After Transcatheter Aortic Valve Replacement in Patients With BAV
Cardiology/Cardiovascular Surgery•
PrevCardioOncAI: Machine Learning Algorithms for Predicting Cardiovascular Disease in Cancer Survivors
Cardiology/Cardiovascular Surgery•
Assessing ChatGPT as an Educational Tool for Image Generation in Dermatology
Dermatology•
Melan-Dx: a knowledge-enhanced vision-language framework improves differential diagnosis of melanocytic neoplasm pathology
Dermatology•
Is ChatGPT a reliable informant? Dermatologists review AI-generated answers to frequently asked questions about melanoma
Dermatology•
Skin disease diagnostics through federated transfer learning on heterogeneous data
Dermatology•
Predictive analytics for de novo malignancies after lung transplantation
Dermatology•
Transcriptomic profiling and machine learning uncover gene signatures of psoriasis endotypes and disease severity
Dermatology•
Domain-Specific and Computer-Vision-Driven Versus General-Purpose AI Models in PA-CXR Analysis: a Comparative Study with Emergency-Medicine Specialists
Emergency Medicine•
Early mortality prediction after severe trauma using ensemble machine learning: a single-center retrospective study
Emergency Medicine•
Improving In-person Interpreter Utilization in Complex Care: Findings from a Stepped-Wedge Cluster Randomized Trial of Integrated Artificial Intelligence
Emergency Medicine•
A Machine Learning Approach to Predicting Radiographic Outcomes of Nonsurgically Treated Distal Radius Fractures
Emergency Medicine•
Development and validation of risk prediction models for high-risk patients with non-traumatic acute abdominal pain: a prospective observational study
Emergency Medicine•
Natural Language Processing to Assess Palliative Care Processes and Health Care Utilization in Seriously Ill Older Adults with Severe Trauma
Emergency Medicine•
Understanding surgeon adoption of artificial intelligence surgical technology: integrating UTAUT-TOE model
Neurotechnology•
Preoperative MEG reveals differential brain network characteristics in drug-resistant epilepsy patients based on vagus nerve stimulation response
Neurotechnology•
Neuromodulation techniques for enhancing lower extremity motor function in children with cerebral palsy (CP): a systematic review and meta-analysis of repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS) interventions
Neurotechnology•
Adolescent and adult stress alter excitatory-inhibitory network dynamics in the medial prefrontal cortex
Neurotechnology•
From data to diagnosis: A comprehensive review of machine learning-driven wearable sensors in healthcare
Neurotechnology•
A programmable peptide interface for on-demand neural culturing platforms
Neurotechnology•
Evaluation of the outcomes of vagal nerve stimulation in children with drug‑refractory epilepsy in South Africa
Neurotechnology•
Effect of cognitive training on cortisol levels in patients with neurocognitive disorders
Neurotechnology•
Advancing the future of prosthetic rehabilitation with Regenerative Peripheral Nerve Interface surgery: Questions and opportunities
Neurotechnology•
Machine learning for endoscopic third ventriculostomy success prediction—a systematic review and meta-analysis
Pediatrics•
Trust at risk: Why public health must lead the use of AI in pandemic preparedness
Public Health•
Machine learning (ML) and deep learning (DL) in vaccine target selection, design, development and characterization
Public Health•
Improving Clinical Decision-Making in Treating Airway Diseases With an Expert System Built Upon the Free AI Tool Google NotebookLM
Public Health•
Interpretable large language models for early prediction of antimicrobial multidrug resistance
Public Health•
Assessment of Physician Preferences for Large Language Model-Generated Responses Across Geographic Regions and Clinical Experience Levels: Preliminary Survey Study
Public Health•
An exploratory study on the relationship between renal cell carcinoma and CAFs infiltration by integrating Pathomics and collagen features
Urology•
Artificial intelligence versus classical scoring systems: a comparative analysis of stone-free prediction after percutaneous nephrolithotomy
Urology•
Machine learning methods for predicting early recurrence in Ta stage bladder cancer and comparison with conventional statistical methods
Urology•
Machine learning methods for predicting early recurrence in Ta stage bladder cancer and comparison with conventional statistical methods
Urology•
Hybrid Population Pharmacokinetic–Machine Learning Modeling to Predict Infliximab Pharmacokinetics in Pediatric and Young Adult Patients with Crohn’s Disease
Pediatrics•
Transcriptomic profiling and machine learning uncover gene signatures of psoriasis endotypes and disease severity
Dermatology•
Advancements in psoriasis classification using custom transfer learning algorithms
Dermatology•
Interpreting free-text cardiac catheterisation reports: A machine learning approach informed by focused ethnography
Cardiology/Cardiovascular Surgery•
Artificial Intelligence–Enabled ECG for Diastolic Dysfunction in Congenital Heart Disease: A Novel Risk Stratification Tool
Cardiology/Cardiovascular Surgery•
Quantitative Coronary Plaque Analysis in Clinical Practice: 2025 ACC Scientific Statement
Cardiology/Cardiovascular Surgery•
Development and validation of a predictive model for depression in patients with advanced stage of cardiovascular-kidney-metabolic syndrome
Psychiatry•
Investigating the role of depression in obstructive sleep apnea and predicting risk factors for OSA in depressed patients: machine learning-assisted evidence from NHANES
Psychiatry•
Machine learning-enhanced mapping of suicide risk in Bipolar Disorder: A multi-modal analysis
Psychiatry•
Machine learning-based predictive modeling of depressive symptoms in Chinese adolescents
Psychiatry•
A novel machine learning-based method to quantify the effect of transcranial direct current stimulation on opioid users
Psychiatry•
Identifying EEG-based neurobehavioral risk markers of gaming addiction using machine learning and iowa gambling task
Psychiatry•
Association of heatwave exposure and multimorbidity with depression trajectories among older adults: evidence from the China Health and Retirement Longitudinal Study
Psychiatry•
Choices of Artificial Intelligence (AI): ChatGPT's Solutions to Ethical Dilemmas in Bipolar Disorder Care
Psychiatry•
From Social to Symbolic: Investigating the Neural Networks Involved in Emoji and Facial Expression Recognition
Neurology•
ADHD Classification with GCN via Joint Feature Learning among Nodes and Edges
Neurology•
Association between cognitive status and structural brain changes in Alzheimer’s disease: Clinical implication of lightweight deep learning-aided diagnosis
Neurology•
Explainable End-to-End Seizure Prediction via Stationary Wavelet Transform-Driven Dynamic Multiscale Fuzzy Clustering
Neurology•
Title: Circulating inflammatory proteins predict dementia risk, are linked to structural brain changes and modifiable risk factors.
Neurology•
A preregistered, Open Pipeline for Early Cerebral Palsy Risk Assessment from Infant Videos
Neurology•
Multimodal diagnosis of Parkinson's disease with an internet-based collaborative agent architecture of medical language models.
Neurology•
The use of fully immersive virtual reality for screening neurodegenerative diseases: A systematic review of behavioral and diagnostic outcomes.
Neurology•
Predicting Alzheimer's Disease Assessment Scale from T1‐weighted MRIs by Fine‐tuning a Pretrained Deep Learning Model
Neurology•
A Multimodal Neuro-Demographic Signature for Immuno-Metabolic Depression
Neurology•
An integrated machine learning framework for developing a transcriptomic analysis and machine learning-based diagnostic model of gout based on sleep disorder-related genes
Neurology•
Multidimensional analysis and predictive modeling of cognitive decline risk in the United States using propensity score matching and machine learning
Neurology•
Two-Minute Deep Learning-Powered Brain Quantitative Mapping: Accelerating Clinical Imaging With Synthetic Magnetic Resonance Imaging.
Neurology•
Multi‐modal Neuroimaging Based Dementia Risk Score for Early Detection of Future Risk of Dementia Onset for Alzheimer's Disease.
Neurology•
Unlocking the silent signals: Motor kinematics as a new frontier in early detection of mild cognitive impairment
Neurology•
A preregistered, Open Pipeline for Early Cerebral Palsy Risk Assessment from Infant Videos
Neurology•
Influence of personalized human head modeling and resolution on EEG source localization for rapid brain mapping
Neurology•
Lasso and XGBoost‐Enabled Prediction Models for Sensory Dysfunction, Biological Age, and APOE Genotype in Cognitive Decline Risk Assessment
Neurology•
Investigating the Utility of Explainable Artificial Intelligence for Neuroimaging-Based Dementia Diagnosis and Prognosis.
Neurology•
Organotypic Retinal Explant Culture as a Model for Neuroretinal Degenerative Disease and Future Applications
Neurology•
ClathPLM: Deep multi-view feature extraction with CNN and attention enhances clathrin protein identification
Neurology•
EEG-based epileptic seizure prediction with patient-tailored spectral–spatial–temporal feature learning
Neurology•
Utilising artificial intelligence to identify surgical anatomy during laparoscopic donor nephrectomy - a validation and feasibility study
Urology•
Comparative Performance of Machine Learning Models in Reducing Unnecessary Targeted Prostate Biopsies
Urology•
Integrating artificial intelligence across the bladder cancer continuum: progress, promise, and pitfalls
Urology•
Comprehensive analysis of key palmitoylation-modifying enzymes in clear cell renal cell carcinoma: implications for prognosis and therapy
Urology•
Behavioral Dynamics of AI Trust and Health Care Delays Among Adults: Integrated Cross-Sectional Survey and Agent-Based Modeling Study
Public Health•
Benchmark evaluation of deepseek AI models in antibacterial clinical decision-making for infectious diseases
Public Health•
Exploring the Role of App Features in Providing Continuity of Care to Users on a Digital Mental Health Platform (Wysa): Retrospective Mixed Methods Observational Study
Public Health•
Social determinants of health to predict health-related quality of life in diabetes patients: explainable machine learning approaches
Public Health•
Transforming Chinese cohort studies through artificial intelligence: a new era of population health research
Public Health•
Large Language Model-Assisted Research Question Development in Public Health: A Case Study in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC)
Public Health•
Digital profile of children's hearts: automated echocardiogram strain analysis facilitates earlier detection of cardiac dysfunction
Pediatrics•
Patient perceptions and attitudes towards the use of artificial intelligence in the symptomatic breast unit
Medical Informatics•
Vitreoretinal disease detection using artificial intelligence: a systematic review and meta-analysis
Medical Informatics•
Application of artificial intelligence in head and neck squamous cell carcinoma
Medical Informatics•
Cardiovascular measures from abdominal MRI provide insights into abdominal vessel genetic architecture
Medical Informatics•
Integrating artificial intelligence (AI) into colorectal cancer reporting
Medical Informatics•
Deep learning for early diagnosis of uveal melanoma: a systematic review and meta-analysis
Oncology•
Transcriptomic subgroups in soft tissue tumors correlate with morphologic subtype, genomic features, and outcome
Oncology•
Adverse event reporting of mirtazapine: A disproportionality analysis of FDA adverse event reporting system (FAERS) database from 2004-2024
Psychiatry•
A machine learning approach for detection of claustrophobic brain activity in electroencephalography
Psychiatry•
To Leave or Stay? Influences on Early Exit and Completion in a New Zealand Residential Drug Rehabilitation Service
Psychiatry•
Intersection of Big Five Personality Traits and Substance Use on Social Media Discourse: AI-Powered Observational Study
Psychiatry•
Towards precision psychiatry: Metabolomics identifies three biological subtypes of depression
Psychiatry•
Artificial intelligence powered mobile health apps for skin cancer detection: current challenges and a systems thinking approach for improved public health outcomes in low- and middle-income countries
Dermatology•
Innovations in skin microphysiological systems for nonclinical testing and FDA modernization
Dermatology•
DermaGPT: A federated multimodal framework with a meta-learned trust function for interpretable dermatology diagnostics
Dermatology•
Multimodal Large Language Models for Inflammatory Skin Disease Evaluation: A Cross-Sectional Study
Dermatology•
Establishing dermatopathology encyclopedia DermpathNet with Artificial Intelligence-Based Workflow
Dermatology•
AI-powered SPOT imaging for enhanced myocardial scar detection and quantification
Cardiology/Cardiovascular Surgery•
Identification of Biomarkers for Right Ventricular Dysfunction in Idiopathic Dilated Cardiomyopathy Via Urinary Proteomics and Machine Learning
Cardiology/Cardiovascular Surgery•
Artificial Intelligence-Enabled ECG for Diastolic Dysfunction in Congenital Heart Disease: A Novel Risk Stratification Tool
Cardiology/Cardiovascular Surgery•
Detecting Bicuspid Aortic Valve From Echocardiographic Reports Using Natural Language Processing: A Veteran Affairs Study
Cardiology/Cardiovascular Surgery•
Comparative Performance of Machine Learning and Traditional Risk Scores in Predicting Adverse Events After Transcatheter Aortic Valve Replacement in Patients With Atrial Fibrillation
Cardiology/Cardiovascular Surgery•
A hybrid spatial and temporal attention driven network for left ventricular function assessment using echocardiography
Cardiology/Cardiovascular Surgery•
Investigating the effect of transcranial magnetic stimulation combined with active sensory training on upper limb motor recovery after stroke: protocol for a randomised, sham-controlled, single-centre trial
Neurotechnology•
An update on the effects of cerebellar transcranial magnetic stimulation on cognitive function
Neurotechnology•
Virtual reality mediated brain-computer interface training improves sensorimotor neuromodulation in unimpaired and post spinal cord injury individuals
Neurotechnology•
Dynamic modulation of corticomuscular coherence during ankle dorsiflexion after stroke: towards hybrid BCI for lower-limb rehabilitation
Neurotechnology•
Impact of dual-tasking and balance confidence on turns and transitions: a cross-sectional study in Parkinson's disease
Neurotechnology•
Noninvasive BCI-based cognitive rehabilitation in poststroke cognitive impairment: study protocol for a randomized controlled trial
Neurotechnology•
Generative Artificial Intelligence for Environmental Assessment: A New Paradigm for Sustainability Analysis
Public Health•
Ethical Risks and Structural Implications of AI-Mediated Medical Interpreting
Public Health•
Disability risk prediction models in community-dwelling older adults: a systematic review
Public Health•
Geospatial modelling for zoonotic disease hotspot identification within a One Health framework: a systematic review
Public Health•
National data meets AI: Machine learning for predicting overweight/obesity among ever-married Bangladeshi women
Public Health•
Development of machine learning prediction models for postoperative outcomes in adult male circumcision
Urology•
A two-stage deep learning framework for kidney disease detection using modified specular-free imaging and EfficientNetB2
Urology•
Granular Machine Learning-Based Computed Tomography Contrast Phase Prediction
Urology•
Gene modification: Exploring the potential in treating kidney diseases
Urology•
Cord blood biomarkers predict neonatal respiratory dysfunction after prenatal smoke exposure: A decision tree model
Pediatrics•
Adoption of Machine Learning in US Hospital Electronic Health Record Systems: Retrospective Observational Study
Emergency Medicine•
Artificial intelligence vs. emergency physicians: who diagnoses better?
Emergency Medicine•
Grouping of Emergency Department-based Cardiac Arrest Patients According to Clinical Features to Assess Patient Outcomes
Emergency Medicine•
Patient attitudes toward ambient artificial intelligence scribes in clinical care: insights from a cross-sectional study
Emergency Medicine•
A meta-learning ensemble framework for robust and interpretable prediction of emergency medical services demand
Emergency Medicine•
Data-driven queueing modelling: a simulation case study of emergency department crowding
Emergency Medicine•
Artificial Intelligence in Cardiopulmonary Resuscitation: Revolutionizing Resuscitation Through Precision and Prediction – A Narrative Review
Emergency Medicine•
Domain-Specific and Computer-Vision-Driven Versus General-Purpose AI Models in PA-CXR Analysis: a Comparative Study with Emergency-Medicine Specialists
Emergency Medicine•
Accuracy is not enough: explainable boosting machine model and identification of candidate biomarkers for real-time sepsis risk assessment in the emergency department
Emergency Medicine•
Evaluation of AI-enhanced tele-ECG response time and diagnosis in acute chest pain patients
Emergency Medicine•
Serum lactate and carboxyhemoglobin as predictors of hyperbaric oxygen therapy in carbon monoxide poisoning: a retrospective study
Emergency Medicine•
Risk Factors for Pediatric Deep Neck Infection Revisit After Emergency Department Discharge for Pharyngitis or Localized Neck Symptoms
Emergency Medicine•
Tacheal intubation vs. supraglottic airway devices during mechanical intra-arrest-ventilation with volume-controlled-ventilation in out-of-hospital cardiac arrest: a cohort study
Emergency Medicine•
Filtered electrocardiogram combined with end-tidal carbon dioxide for the identification of patients’ cardiac arrest status during uninterrupted chest compressions in cardiopulmonary resuscitation
Emergency Medicine•
Development and validation of the Hypotensive Exposure Duration Index for mortality risk prediction in critically ill patients
Emergency Medicine•
Automated Evaluation Framework for AI-Generated Emergency Department Documentation: A Chain-of-Thought Validation Study
Emergency Medicine•
DCEM-TCRCN: an innovative approach to depression detection using wearable IoT devices and deep learning
Psychiatry•
Examining attention-deficit/hyperactivity disorder in endurance and ultra-endurance runners
Psychiatry•
Identifying Key Predictors of Smoking Cessation Success: Text-Based Feature Selection Using a Large Language Model
Psychiatry•
Are clinical improvements in large language models a reality? Longitudinal comparisons of ChatGPT models and DeepSeek-R1 for psychiatric assessments and interventions
Psychiatry•
Classify the fNIRS signals of first-episode drug-naive MDD patients with or without suicidal ideation using machine learning
Psychiatry•
An interpretable approach for schizophrenia classification using fMRI and sMRI features
Psychiatry•
Linking subjective experience of anxiety to brain function using natural language processing
Psychiatry•
Transforming a clinical study database into a structured database adapted to artificial intelligence applications
Medical Informatics•
Multimodal diagnosis of Parkinson’s disease with an internet-based collaborative agent architecture of medical language models
Medical Informatics•
Periodontitis Prediction Model Using Linked Electronic Health and Dental Records
Medical Informatics•
Association of cardiovascular-kidney-metabolic syndrome stages with MASLD prevalence and liver fibrosis severity: evidence from traditional and machine learning approaches
Oncology•
Enhancing therapeutic outcomes with artificial intelligence for HR-positive, HER2-negative metastatic breast cancer
Oncology•
AI-based quantification of tumor-infiltrating lymphocytes with integrative transcriptomics in ovarian clear cell carcinoma: JGOG3025-TR1/A1 study
Oncology•
Establishing dermatopathology encyclopedia DermpathNet with Artificial Intelligence-Based Workflow
Dermatology•
A clinical decision support system for skin cancer classification using fractional gooseneck barnacle-enabled ensemble classifier
Dermatology•
Kaposi's sarcoma in individuals living with HIV: comparative assessment of AI-based clinical responses using a standardized questionnaire set
Dermatology•
Artificial intelligence–enabled precision medicine for inflammatory skin diseases
Dermatology•
A comprehensive comparison of convolutional neural network and visual transformer models on skin cancer classification
Dermatology•
Hybrid vision transformer and graph neural network model with region-adaptive attention for enhanced skin cancer prediction
Dermatology•
A Novel Tool for Predicting Malignant Disease in Adult Patients with Dermatomyositis
Dermatology•
Evaluation and Enhancement of the Prognostic Ability of the Eighth Edition of TNM Staging in Cutaneous Malignant Melanoma: A Population-Based Study of 111,817 Cases Using Machine Learning
Dermatology•
Real-life benefit of artificial intelligence-based fracture detection in a pediatric emergency department
Orthopedics•
Computational analysis of L4–L5 interspinous process devices and interbody fusion spacers using ceramic and polymeric materials via finite element modeling and artificial intelligence
Orthopedics•
YOLOv12 Algorithm-Aided Detection and Classification of Lateral Malleolar Avulsion Fracture and Subfibular Ossicle Based on CT Images: Multicenter Study
Orthopedics•
Application of artificial intelligence in the diagnosis of scaphoid fractures: impact of automated detection of scaphoid fractures in a real-life study
Orthopedics•
Performance of artificial intelligence in automated measurement of patellofemoral joint parameters: a systematic review
Orthopedics•
Predicting Thoracolumbar Vertebral Osteoporotic Fractures: Value Assessment of Chest CT-Based Machine Learning
Orthopedics•
Prediction of lumbar disc degeneration based on interpretable machine learning models: retrospective cohort study
Orthopedics•
A deep learning-based framework for standardized analysis of trabecular bone compartments from micro-CT imaging data in the mouse tibia
Orthopedics•
Radiomics-based machine learning model integrating preoperative vertebral computed tomography and clinical features to predict cage subsidence after single-level anterior cervical discectomy and fusion with a zero-profile anchored spacer
Orthopedics•
Assessing deep learning artificial intelligence support for detecting elbow fractures in the pediatric emergency department
Orthopedics•
Augmenting a ResNet + BiLSTM Deep Learning Model with Clinical Mobility Data Helps Outperform a Heuristic Frequency-Based Model for Walking Bout Segmentation
Orthopedics•
Is orthopaedics entering the age of generative AI?—A narrative review of current applications, challenges, and future directions
Orthopedics•
Towards streamlining orthopedic consultations: Machine learning classification of knee diagnosis groups via computer-assisted history taking
Orthopedics•
Deep learning-based prediction of cervical canal stenosis from mid-sagittal T2-weighted MRI
Orthopedics•
Tracking temporal progression of benign bone tumors through X-ray based detection and segmentation
Orthopedics•
Development of a Machine Learning Model for Determining Alignment in Knees Following Total Knee Arthroplasty
Orthopedics•
Development and Validation of Interpretable Machine Learning Models Incorporating Paraspinal Muscle Quality to Predict Cage Subsidence Risk Following Posterior Lumbar Interbody Fusion
Orthopedics•
Automated detection of mandibular landmarks in CT data using a dual-input approach in a two-stage design
Orthopedics•
External validation of an artificial intelligence tool for fracture detection in children with osteogenesis imperfecta: a multireader study
Orthopedics•
Measuring provider-level differences in perioperative workflow using computer vision-based artificial intelligence
Orthopedics•
Radiomics-based classification of medication-related osteonecrosis of the jaw using panoramic radiographs
Orthopedics•
High patient and surgeon satisfaction with ChatGPT-generated responses to real patient questions regarding total knee arthroplasty
Orthopedics•
Automated 3D segmentation of rotator cuff muscle and fat from longitudinal CT for shoulder arthroplasty evaluation
Orthopedics•
Insights From Inputs: Enhancing Revision Total Joint Arthroplasty Resource Allocation With Machine Learning Prediction
Orthopedics•
Garden classification of femoral neck fracture using deep-learning algorithm
Orthopedics•
Automatic opportunistic osteoporosis screening using chest X-ray images via deep neural networks
Orthopedics•
Pelvic Incidence-Dependent Clustering of Sagittal Spinal Alignment in Asymptomatic Middle-Aged and Elderly Adults: A Machine Learning Approach
Orthopedics•
Synthetic health data in Canada: A scoping review of methods, applications, and data sources
Public Health•
Comprehensive Pediatric Health Risk Stratification Using an AI-Driven Framework in Children Aged 2 to 8 Years: Design and Validation Study
Public Health•
How ready are we to use artificial intelligence in our fight against antimicrobial resistance? An ESGAID and EAAS perspective
Public Health•
Ethical Risks and Structural Implications of AI-Mediated Medical Interpreting
Public Health•
A review of AI/ML approaches in wastewater surveillance advancement
Public Health•
Fast prostate MRI learning curves in urology and radiology residents: beware of overinterpreting
Urology•
Prediction of Prostate Cancer Biochemical Recurrence After Radical Prostatectomy by Collagen Models Using Multiomic Profiles
Urology•
A perturbed multilayer perceptron approach to predicting distant metastatic sites of cancer patients
Oncology•
Immunotherapy in Triple-Negative Breast Cancer: From Molecular Mechanisms to Precision Medicine-Overcoming Resistance and Optimizing Clinical Outcomes
Oncology•
Early wounds, delayed consequences: Brain-behavior modeling reveals neural pathways linking childhood trauma to procrastination
Psychiatry•
Predicting rTMS treatment response in schizophrenia using interpretable machine learning: a SHAP-based analysis.
Psychiatry•
Association Between Age-Specific Sleep Sufficiency and Autism Spectrum Disorder in U.S. Children
Psychiatry•
Leveraging low-cost app-based step count data to assess depression and anxiety in university students: A cross-sectional mobile health study
Psychiatry•
Machine learning-based analysis and prediction of factors influencing mental health among children and adolescents in Jiangsu Province
Psychiatry•
Integrating explainable AI with clinical features to enhance ADHD diagnostic understanding
Psychiatry•
Artificial intelligence-generated synthetic data for cancer research and clinical trials
Medical Informatics•
Ethical dilemmas in the use of artificial intelligence in transfusion medicine
Medical Informatics•
An agentic system for rare disease diagnosis with traceable reasoning
Medical Informatics•
Different BI-RADS breast cancer diagnosis using MobileNetV1 and vision transformer based on explainable artificial intelligence (XAI)
Medical Informatics•
Magnetic resonance imaging-based proton dose calculation for pelvic tumors using deep learning
Medical Informatics•
Prospective quantitative analysis of hyperparameter and input optimization in GPT-5: comparative contribution to radiologist performance in abdominal radiology
Medical Informatics•
Artificial intelligence for the prediction of synchronous and metachronous liver metastasis in colorectal cancer patients: a systematic review and meta-analysis
Medical Informatics•
Hybrid vision transformer and graph neural network model with region-adaptive attention for enhanced skin cancer prediction
Dermatology•
A Novel Tool for Predicting Malignant Disease in Adult Patients with Dermatomyositis
Dermatology•
Evaluation and Enhancement of the Prognostic Ability of the Eighth Edition of TNM Staging in Cutaneous Malignant Melanoma: A Population-Based Study of 111,817 Cases Using Machine Learning
Dermatology•
Three dimensional total body photography identifies cutaneous phenotypes associated with late-onset invasive melanoma risk
Dermatology•
AI and Digital Tools in Dermatology: Addressing Access and Misinformation Journal: JMIR Dermatology
Dermatology•
Static and dynamic low- and high-order brain functional network modulations by tDCS in children with autism spectrum disorder
Neurotechnology•
Pitching-specific facilitation of upper-limb corticospinal excitability during motor imagery of sports motor skills
Neurotechnology•
Diagnostic yield and safety of frame-based versus robot-assisted stereotactic brain biopsy: a matched cohort analysis
Neurotechnology•
Dynamic modulation of corticomuscular coherence during ankle dorsiflexion after stroke: towards hybrid BCI for lower-limb rehabilitation
Neurotechnology•
Brain-computer interfaces in poststroke rehabilitation: a meta-analysis of randomized clinical trials
Neurotechnology•
Leveraging wearable haptics for guidance in virtual rehabilitation: effects on motor control from an immersive VR setting
Neurotechnology•
Modulating inhibitory control in test-anxious individuals via tDCS: An ERP study
Neurotechnology•
Explainability in AI-enabled medical neurotechnology: a scoping review
Neurotechnology•
Differential effects of focused ultrasound neuromodulation in Parkinson's disease mice versus healthy mice
Neurotechnology•
The impact of vagus nerve stimulation on the most disabling seizures: A retrospective study in adults with drug-resistant epilepsy
Neurotechnology•
M3T-attention: a multi-level multi-scale temporal attention transformer for EEG hand movement trajectory decoding
Neurotechnology•
Effects of computerized cognitive training on brain function in children with ADHD: A longitudinal neuroimaging study based on fALFF
Neurotechnology•
Artificial intelligence in electrocardiogram signals for sudden cardiac death prediction: a systematic review and meta-analysis
Cardiology/Cardiovascular Surgery•
Artificial intelligence-enhanced electrocardiogram for arrhythmogenic right ventricular cardiomyopathy detection
Cardiology/Cardiovascular Surgery•
ISENet: a Deep Learning Model for Detecting Ischemic ST Changes in Long-Term ECG Monitoring
Cardiology/Cardiovascular Surgery•
Artificial Intelligence and Big Data Technologies in the Construction of Surgical Risk Prediction Model for Patients with Coronary Artery Bypass Grafting
Cardiology/Cardiovascular Surgery•
Deep Learning-Based Prediction Model for Cardiac Resynchronization Therapy Responders Using Electrocardiogram Data
Cardiology/Cardiovascular Surgery•
Interpretable machine learning models for predicting in-hospital and 30 days adverse events in acute coronary syndrome patients in Kuwait
Cardiology/Cardiovascular Surgery•
Electrocardiogram screening for aortic valve stenosis using artificial intelligence
Cardiology/Cardiovascular Surgery•
Prognostic models for patients suffering a heart failure with a preserved ejection fraction: a systematic review
Cardiology/Cardiovascular Surgery•
Artificial intelligence aids doctors in diagnosing necrotizing enterocolitis and predicting surgery using abdominal radiographs: a multicenter study
Pediatrics•
Interpreting Deep Learning-Based Prediction of the BRAF V600E Mutation Using Diagnostic Whole Slide Images in Skin Cutaneous Melanoma
Dermatology•
Artificial intelligence-based method for detecting wrist fractures in children
Pediatrics•
Performance of Large Language Models in the Japanese Public Health Nurse National Examination: Comparative Cross-Sectional Study
Public Health•
Prediction of COVID-19 hospitalisation, ICU admission or death following ChAdOx1 vaccination using artificial intelligence: A clinical predictive model from the English RAVEN study
Public Health•
Enhancing prostate cancer diagnosis: a machine learning-based biomarker approach
Urology•
Survival Prediction in Patients With Bladder Cancer Undergoing Radical Cystectomy Using a Machine Learning Algorithm: Retrospective Single-Center Study
Urology•
Sleep disturbance recorded via wearable sensors predicts depression severity 9 years later
Psychiatry•
Modeling the empathy-self-discovery paradox in Gen Z social behavior with NPD using artificial neural networks
Psychiatry•
Identifying past-year self-reported suicidality in outpatients with somatic symptom disorder using an interpretable machine-learning model: a multicenter study with an online calculator
Psychiatry•
Evaluating ChatGPT-generated psychoeducation for mood disorders: comparative insights from patients and mental health professionals
Psychiatry•
Fast and reliable machine learning-based detection of postoperative intracranial infections in brain tumor patients: a diagnostic study using routine CSF parameters
Oncology•
Computationally Assisted Patient Finding for Navigation to Optimize Pancreatic Cancer Care Access
Oncology•
CXCL9 as a key feature for deep learning-based immune subtyping and prediction of immune checkpoint blockade response in triple-negative breast cancer.
Oncology•
Quantitative CT and Artificial Intelligence in Chronic Lung Disease
Medical Informatics•
Artificial intelligence in paediatric neuroradiology: current landscape, challenges, and future directions
Medical Informatics•
Artificial intelligence in pediatric nephrology: current applications and emerging frameworks for evidence generation
Medical Informatics•
AI-Generated Diet and Exercise Recommendations for Cardiovascular Health Compared to Established Cardiology Society Guidelines
Cardiology/Cardiovascular Surgery•
Artificial Intelligence-Enhanced Electrocardiogram for the Early Detection of Cardiac Amyloidosis
Cardiology/Cardiovascular Surgery•
C-X-C Motif Chemokine Ligand 3 as a Potential Biomarkerfor Diagnosis and Prognosis of Diabetic Kidney Disease
Urology•
Single-cell transcriptomics and machine-learning reveal M1 macrophage-driven progression from minimal change disease to focal segmental glomerulosclerosis
Urology•
Leveraging Machine Learning to Uncover Ethnic-Specific Predictors of Maternal Postpartum Depression
Public Health•
Neural parameter calibration for dengue outbreak forecasting
Public Health•
Artificial intelligence–based quantification of breast arterial calcifications to predict cardiovascular morbidity and mortality
Medical Informatics•
Artificial Intelligence in Mammography Screening: A Narrative Review of Progress, Pitfalls, and Potential
Medical Informatics•
Silent struggles: a machine learning approach for predicting suicidal ideation based on crisis symptoms and childhood trauma in Saudi adolescents
Psychiatry•
Predicting Treatment Response in Female Adolescents With Non-Suicidal Self-Injury Using Neurophysiological Biomarkers and Machine Learning
Psychiatry•
Using machine learning to identify parenting features prospectively related to callous-unemotional traits from infancy to early adolescence
Psychiatry•
Integrating spatial lymph node patterns and multimodal clinicopathological features to predict post-neoadjuvant recurrence in gastric adenocarcinoma: a machine learning nomogram
Oncology•
CRISPR-Cas12a/Cas13a in cancer molecular diagnosis
Oncology•
Assessment of Positive Cardiac Remodeling in Hypertrophic Obstructive Cardiomyopathy Using an Artificial Intelligence–Based Electrocardiographic Platform in Patients Treated With Mavacamten
Cardiology/Cardiovascular Surgery•
Predicting Outcomes in Patients With Tricuspid Regurgitation Undergoing Transcatheter Edge-to-Edge Repair Using an Artificial Intelligence-Derived Risk Score: The EuroTR Risk Score
Cardiology/Cardiovascular Surgery•
Temporal Validation of a Machine Learning Readmission Model in Heart Failure With Preserved Ejection Fraction and Chronic Kidney Disease
Cardiology/Cardiovascular Surgery•
Assessing public interest in artificial intelligence in dermatology: A Google Trends analysis
Dermatology•
ChatGPT-4o as a diagnostic tool for skin cancer: Diagnostic accuracy in melanoma and non-melanoma detection
Dermatology•
Personalized Surveillance in Giant Congenital Melanocytic Nevus, Including the Role of AI, Histopathology and MC1R Genotyping: A Case Report
Dermatology•
Single-cell transcriptomics and machine-learning reveal M1 macrophage-driven progression from minimal change disease to focal segmental glomerulosclerosis
Urology•
Construction of interpretable machine-learning diagnostic models for erectile dysfunction based on routine blood and biochemical detection data
Urology•
Exploration of neutrophil-associated genes in the prognosis of bladder urothelial carcinoma based on a machine learning and multi-omics data integration framework
Urology•
A BEACON for Novel Disease Threats: Leveraging Artificial Intelligence for Informal Event-Based Outbreak Surveillance
Public Health•
Improving Pandemic Prediction: Integrating Physics-Informed Neural Networks and Symbolic Regression for COVID-19 Modeling
Public Health•
Smart Kiosk for Nutritional Management of People With Diabetes in Underserved Communities: Development and Technical Evaluation
Public Health•
SynthEHR-eviction: enhancing eviction SDoH detection with LLM-augmented synthetic EHR data
Public Health•
Ecological and socioeconomic factors associated with globally reported tick-borne viruses
Public Health•
Predictive biomarkers of response to immune checkpoint inhibitors in mismatch repair-deficient endometrial cancer
Oncology•
Development and Validation of an Automated Pediatric Cancer Staging Calculator Using the Toronto Pediatric Cancer Stage Guidelines
Oncology•
Technologies used in Parkinson’s disease: a meta-analysis of their effect on health-related quality of life
PM&R•
Analysis of language patterns in schizophrenia based on natural language processing
Psychiatry•
Identifying psychiatric manifestations in outpatients with depression and anxiety: a large language model-based approach
Psychiatry•
Using AI to Train Future Clinicians in Depression Assessment: Feasibility Study
Psychiatry•
Artificial intelligence and photon‐counting CT: the three phases of the software–hardware revolution in radiology
Medical Informatics•
Artificial intelligence–Driven detection and decision support system for precision management of maize downy mildew
Medical Informatics•
A longitudinal single-cell atlas to predict outcome and toxicity after BCMA-directed CAR T cell therapy in multiple myeloma
Medical Informatics•
Noninvasive skin imaging of melanocytic and nonmelanocytic tumours: recent findings
Dermatology•
Dysfunction of GABAergic interneurons underlies altered neural network oscillations associated with epileptiform activity in PPT1-deficient mice.
Neurology•
Microfluidics-guided localized low-temperature modulation of axonal signal propagation.
Neurology•
Optimized cortical EEG modeling for Parkinson disease diagnosis with snow Shepherd Stride tuning mechanism
Neurology•
Integrating standard and native spaces for radiomics and brain network analysis in Alzheimer's disease diagnosis and prognosis.
Neurology•
An interpretable machine learning framework with data-informed imaging biomarkers for diagnosis and prediction of Alzheimer’s disease
Neurology•
An MRI-based macro- and microstructural neuroimaging-wide association study of subsequent cognitive impairment.
Neurology•
Artificial Intelligence-based detection of neuropsychiatric lupus: an exploratory meta-analysis of neuroimaging and multimodal biomarker models.
Neurology•
VSSI(2p)-Net: Physics-guided deep unfolding with L(2p)-norm and variation sparsity for EEG source imaging
Neurology•
Performance of machine learning algorithms in diffusion tensor imaging of movement disorders: an exploratory meta-analysis
Neurology•
Noise in the diagnosis of epilepsy by experts
Neurology•
Role of neuroimaging markers on predicting of idiopathic intracranial hypertension
Neurology•
A brain-constrained neural model of cognition and language with NEST: transitioning from the Felix framework
Neurology•
Brain imaging reveals hierarchical topology changes and stage-dependent impairments in autoimmune encephalitis
Neurology•
Co-simulation framework combining a microscopically detailed point neuron model of the hippocampal CA1 region with the macroscopic high-resolution virtual brain model
Neurology•
Sleep disturbances and Alzheimer’s disease: a multiscale approach from exposome to neurobiology and precision medicine
Neurology•
AI in epilepsy neuroimaging
Neurology•
No Normal Brain: How Demographic Exclusion Undermines Neuroimaging AI Validity
Neurology•
Investigating Time Distortion in Parkinson's Disease Considering Impaired Frontoparietal Network and Changes in the Brain Dynamic.
Neurology•
Serum metabolomic signatures of relapse recovery in early multiple sclerosis
Neurology•
Cerebrovascular CTA radiomics for objective collateral grading in acute ischemic stroke
Neurology•
A lightweight depthwise separable convolution and channel attention based GRU network for multichannel EEG seizure detection
Neurology•
Predictive modeling of vocal biomarkers for the diagnosis of Parkinson’s disease
Neurology•
Identification of novel biomarkers for Alzheimer's disease: A deep learning omics-based approach to drug pair discovery and exploration of potential therapeutic targets
Neurology•
Bias and generalizability of brain age prediction models: A multi-cohort evaluation with anatomical and interpretability insights
Neurology•
Artificial Intelligence-Based Analysis of Central Nervous System Vasculopathy in Pediatric Sickle Cell Anemia.
Neurology•
Enhancing dementia risk prediction with heart rate and machine learning in the Canadian Longitudinal Study on Aging
Neurology•
Enhancing dementia risk prediction with heart rate and machine learning in the Canadian Longitudinal Study on Aging
Neurology•
Development and efficacy testing of an artificial intelligence enabled treatment package (eDOSTHI) for tobacco cessation: study protocol for a randomized controlled trial
Public Health•
Important Ethical, Technical, and Epidemiological Considerations in an AI Tool Production (ETEPAI): Scoping Review
Public Health•
Integration of Artificial Intelligence in Biosensors for Enhanced Detection of Foodborne Pathogens
Public Health•
Identifying Early Signals From Emerging Public Health Events Using Natural Language Processing.
Public Health•
Impact of quality routine health data utilisation on health service delivery outcomes in low-income and middle-income countries: a systematic review protocol
Public Health•
Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network
Cardiology/Cardiovascular Surgery•
Opportunistic Detection of Coronary Artery Calcium on Noncardiac Chest Computed Tomography: An Emerging Tool for Cardiovascular Disease Prevention: A Scientific Statement From the American Heart Association
Cardiology/Cardiovascular Surgery•
Clinical evaluation of a motion correction software based on partial angle reconstruction in coronary CT angiography
Cardiology/Cardiovascular Surgery•
Machine learning-based prediction of sudden cardiac death in the general population using electronic health record data
Cardiology/Cardiovascular Surgery•
Machine learning based prediction of medication adherence in heart failure using large electronic health record cohort with linkages to pharmacy-fill and neighborhood-level data
Cardiology/Cardiovascular Surgery•
Risk prediction modelling of 30-day all-cause mortality following percutaneous coronary intervention in an Australian population: leveraging machine learning
Cardiology/Cardiovascular Surgery•
AI-Enhanced Predictive Modeling for Identifying Depression and Delirium in Cardiovascular Patients Scheduled for Cardiac Surgery
Cardiology/Cardiovascular Surgery•
Multimodal deep learning for objective skill assessment in robot-assisted vesico-urethral anastomosis
Urology•
ERBB2 as a Prognostic Biomarker in Prostate Cancer: Integration of Single-Cell Transcriptomics, Deep Learning, and Immunohistochemical Validation
Urology•
Robotic credentialing and simulation-based training: An institutional perspective
Urology•
Public Transcriptomic Data Mining for SCLC: From Candidate Ma rkers to Therapeutic Exploration
Oncology•
International testing and refinement of AI algorithms predicting acute leukemia subtypes from routine laboratory data
Oncology•
A 13-gene prognostic model developed using machine learning to predict the response to neoadjuvant chemoradiotherapy in rectal carcinoma
Oncology•
Patient Perceptions of Artificial Intelligence in Diabetes Self-Management: Cross-Sectional Survey Study
PM&R•
Kenyan Neonatal Mortality Risk Predictor: Protocol for a User-Centered Design Evaluation
Public Health•
Severe COVID-19 in the Republic of Korea: Epidemiology, Risk Factors, Therapeutics, and Prognostic Models From Nationwide Data
Public Health•
Predicting low oxygen in patients with acute COVID-19 infection isolating at home: a clinical prediction model
Public Health•
Explainable Machine Learning for Assessing Digital Health Literacy in Older Adults: Validation and Development of a Two-Stage Model Integrating Performance-Based and Self-Assessed Indicators
Public Health•
Single-cell transcriptomic analysis and machine learning identify ATAD3A as a key gene that stabilizes mitochondrial-endoplasmic reticulum membranes, promoting bladder cancer progression
Urology•
Machine learning derived proliferating T cell-related signature: a novel biomarker for prognosis and treatment efficacy in clear cell renal cell carcinoma
Urology•
Artificial intelligence in neurology practice: promise, perils, and a roadmap for responsible integration
Medical Informatics•
An artificial intelligence-powered digital pathology platform to support large-scale deworming programs against soil-transmitted helminthiasis and intestinal schistosomiasis in resource-limited settings
Medical Informatics•
A Pilot Study to Evaluate Artificial Intelligence-Driven Early Retrieval of Medical Histories in the Emergency Department
Medical Informatics•
Using Generative Artificial Intelligence for Healthcare-Associated Infection Surveillance
Medical Informatics•
Artificial Intelligence in hepatology: A position paper by the Italian Association for the Study of the Liver
Medical Informatics•
A Strategic Partnership to Advance AI Applications in Genomics and Bioinformatics for Health Innovation
Medical Informatics•
Artificial intelligence guided occlusion reconstruction in nonoccluding CBCT: A validation study
Medical Informatics•
Artificial intelligence and radiomics in bladder cancer MRI: a scoping review of applications, performance, and barriers to clinical translation
Medical Informatics•
Cutting-edge AI technologies in skin cancer applications
Medical Informatics•
Artificial Intelligence for Cardiovascular Risk Prediction: An Umbrella Review of Applications and Translational Challenges
Medical Informatics•
Advancements in bone marrow biopsy: the role of omics and artificial intelligence in hematologic diagnostics
Medical Informatics•
Evaluating ChatGPT-4 as a digital patient education tool in anesthesia: A multi-rater quality assessment
Anesthesiology•
Systematic review of Artificial Intelligence-based methods for glycemic control and risk prediction in intensive care units
Anesthesiology•
Postoperative New-Onset Heart Block in Noncardiac Surgery: Model Development, Validation, and Long-Term Prognostic Analysis
Anesthesiology•
Artifical Intelligence in Predicting Surgical Problems and Postoperative Morbidity in Mandibular Third Molar Extractions
Anesthesiology•
Automating Critical Care EEG: Enhancing Accuracy, Efficiency, and Patient Outcomes in Critical Care
Anesthesiology•
Machine Learning in the ICU: Predicting Mortality in Patients with Carbapenem-Resistant Gram-Negative Bacilli Bloodstream Infections
Anesthesiology•
Application of Artificial Intelligence in Chronic Pain: Bibliometric Analysis
Anesthesiology•
Understanding anesthesia anxiety: A mixed-methods analysis of propofol discourse on reddit
Anesthesiology•
Development and internal validation of a therapeutic effect predictive model for myofascial pain syndrome
Anesthesiology•
Advanced machine learning approaches for predicting Neglected Tropical Disease co-endemicity in Kenya: A focus on soil-transmitted helminths, schistosomiasis, and lymphatic filariasis
Public Health•
DengueGNN: Graph-based deep learning for modeling disease spread dynamics and prediction
Public Health•
Prediction model for additional procedure requirement in flexible ureterorenoscopy using explainable artificial intelligence
Urology•
Study of bladder cancer detection in standard white light versus AI-supported endoscopy-01 (RAISE-01) – Development and validation of an AI-based support too
Urology•
Agentic AI for Prostate Cancer: A Vision for Multimodal Clinical Intelligence
Oncology•
A Review of Automatic Hair Removal in Dermoscopy Images: From Image Processing to Deep Learning
Dermatology•
Artificial intelligence algorithm to predict the requirement of neonatal endotracheal intubation within 3 h: application for clinical practice
Anesthesiology•
Explainable Machine Learning for Prediction of Early Postoperative Nausea and Vomiting After General Anesthesia
Anesthesiology•
Interpretable machine learning prediction models for 28-day mortality in critically ill patients with atrial fibrillation and acute kidney injury
Anesthesiology•
AI-Assisted Dialysis Decision-Making: Assessing Agreement Between ChatGPT and Nephrologist in Initial Dialysis Indication and Prescription in Emergency and ICU Settings
Anesthesiology•
Utilization and Feasibility of a Wearable Device in Patients With Sedative Effects of Drugs: Protocol for a Prospective Observational Study for the Advanced Respiratory Monitoring Events in Drug Toxicity (ARM-ED) Study
Anesthesiology•
Development of a Classifier for Metabolic Subtypes of Nasopharyngeal Carcinoma to Guide Personalized Immunotherapy Strategies: Biomarker Analysis of the Phase III CONTINUUM and DIPPER Trials
Oncology•
AI-based modeling of treatment decisions in benign prostatic hyperplasia: a transformer-based comparative study
Urology•
Artificial Intelligence in Intraoperative Imaging and Navigation for Spine Surgery: A Narrative Review
Medical Informatics•
The landscape of artificial intelligence-enabled medical devices in the EU and the US intended for intensive care units
Medical Informatics•
Machine learning prediction model for delirium after heart valve replacement with cardiopulmonary bypass: A large-scale cohort study
Cardiology/Cardiovascular Surgery•
Automated Echocardiographic Detection of Congenital Heart Disease Using Artificial Intelligence
Cardiology/Cardiovascular Surgery•
Machine-learning approach on echocardiography to improve the detection of transthyretin amyloid cardiomyopathy: GRAAL algorithm.
Cardiology/Cardiovascular Surgery•
Deep learning of echocardiography distinguishes between presence and absence of late gadolinium enhancement on cardiac magnetic resonance in patients with hypertrophic cardiomyopathy
Cardiology/Cardiovascular Surgery•
A responsible AI framework for infection surveillance in low-resource settings: ethics, opportunities and threats for LMICs (EOT-LMICs)
Public Health•
Comparison of Artificial Intelligence Tools With Human Coding for Sentiment, Topic, and Thematic Analysis Tasks of Public Health Datasets During the COVID-19 Pandemic in Australia: Case Study
Public Health•
Ethical AI innovation in healthcare and sustainable development in Bangladesh
Public Health•
Imaging Modalities in Tuberculosis
Public Health•
Development and validation of machine learning prognostic models for overall survival in non-surgical prostate cancer patients with bone metastases
Urology•
Oxidative stress reprograms benign prostatic hyperplasia microenvironments: insights from integrative multi-omics and machine learning
Urology•
AI-Driven Pathology and Blood-Based Biomarkers: A Golden Opportunity to Democratize Precision Oncology
Medical Informatics•
Evaluating deep learning sepsis prediction models in ICUs under distribution shift: a multi-centre retrospective cohort study
Anesthesiology•
Implementation and learning curve in AI-assisted fluid management during abdominal oncologic surgery: a retrospective observational study
Anesthesiology•
Machine learning models for predicting postoperative paraplegia in acute type A aortic dissection patients
Anesthesiology•
Reflection on the Integration of Artificial Intelligence in Anaesthesiology: Beyond Algorithmic Performance
Anesthesiology•
Modulation of the Vasopressin System in Distributive and Cardiogenic Shock: Theoretical Principles and Practical Applications
Anesthesiology•
Explainable machine learning for postoperative respiratory failure prediction in open-heart surgery patients — a study based on the MIMIC-IV database
Anesthesiology•
Machine learning models for predicting postoperative paraplegia in acute type A aortic dissection patients
Anesthesiology•
Reflection on the Integration of Artificial Intelligence in Anaesthesiology: Beyond Algorithmic Performance
Anesthesiology•
Modulation of the Vasopressin System in Distributive and Cardiogenic Shock: Theoretical Principles and Practical Applications
Anesthesiology•
Explainable machine learning for postoperative respiratory failure prediction in open-heart surgery patients — a study based on the MIMIC-IV database
Anesthesiology•
Development of a machine learning algorithm model to predict intraoperative hypotension in elderly patients undergoing thoracic and abdominal surgeries
Anesthesiology•
Determinants of labor epidural analgesia uptake and associations with maternal-neonatal outcomes: a stratified cohort study with risk prediction modeling
Anesthesiology•
Explainable machine learning using urinary metabolomics to predict pediatric sepsis-associated acute kidney injury: a two-center prospective observational study
Anesthesiology•
A systematic comparison of ChatGPT and DeepSeek for guideline-based question answering in obstetric anesthesia
Anesthesiology•
Modeling Diabetes Risk and Progression With Public Health Data: Ontology-Guided, Simulation-Capable Digital Twin Study
Public Health•
Imaging Modalities in Tuberculosis
Public Health•
Comparison of OneChoice AI-based clinical decision support recommendations with infectious disease specialists and non-specialists for bacteremia treatment in Lima, Peru
Public Health•
Modeling Diabetes Risk and Progression With Public Health Data: Ontology-Guided, Simulation-Capable Digital Twin Study
Public Health•
Development and validation of an ensemble machine learning model to predict survival in locally advanced rectal cancer: A multicenter, retrospective study
Oncology•
Identifying a fatty acid metabolic gene signature in diabetic cardiomyopathy through integrated bioinformatics and machine learning
Medical Informatics•
Harnessing big data and artificial intelligence in transfusion medicine: Opportunities for precision, safety and efficiency
Medical Informatics•
Development and validation of a minimally invasive diagnostic model for biliary atresia using artificial intelligence
Pediatrics•
Macro Habitat-Based T2-Weighted MRI Radiomics and Deep Learning Fusion for Predicting Treatment Response and Prognosis After Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer
Oncology•
Integrating AI Into Governmental Public Health Decision Making: Challenges, Considerations, and a Path Forward
Public Health•
Evaluating large language model performance in answering “Principles of Health” course questions
Public Health•
Machine learning models in anaesthesiology: bridging the gap from model training to implementation
Anesthesiology•
Artificial intelligence in airway management: a narrative review
Anesthesiology•
Navigating the medicolegal landscape of artificial intelligence in anaesthesia and peri-operative medicine
Anesthesiology•
An explainable clinical–radiomics machine learning model for preoperative prediction of WHO/ISUP nuclear grade in clear cell renal cell carcinoma
Anesthesiology•
Decoding the OR Black Box and Similar Technologies and Considerations in Otolaryngologic Surgery
Anesthesiology•
The Rise in Artificial Intelligence and Machine Learning Models to Screen for Cleft-Related Velopharyngeal Dysfunction: A Systematic Review
Medical Informatics•
Systematic reviews of low-frequency repetitive transcranial magnetic stimulation on cognition and epileptiform discharge in patients with epilepsy
Neurotechnology•
Early-stage findings on long-term behavioral effects of Transcranial Magnetic Stimulation in cortical blindness in rats
Neurotechnology•
Rescue Thalamotomy for Habituation to Deep Brain Stimulation in Essential Tremor: Case Report
Neurotechnology•
Transcutaneous vagus nerve stimulation enhances episodic memory across valences and memory stages
Neurotechnology•
Vagus nerve stimulation for drug-resistant epilepsy and predictors for seizure freedom: A nationwide multicenter cohort study in Mexico
Neurotechnology•
Approach Motivation and Reward Sensitivity: Effects of High‐Definition Transcranial Direct Current Stimulation (HD‐tDCS) to Brain Hemispheres on Effort‐Related Cardiovascular Response
Neurotechnology•
BCI sports: exploring the potential of BCI-leveraged sport participation for children with quadriplegic cerebral palsy
Neurotechnology•
Neurotechnological cognitive enhancement and human rights: a complex dynamic between empowerment and constraint
Neurotechnology•
Anesthetic Management of Patients for Vagal Nerve Stimulator Placement: A Narrative Review
Neurotechnology•
Motor imagery EEG signal classification using minimally random convolutional kernel transform and hybrid deep learning
Neurotechnology•
Brain-Adhesive Bioelectronics With Shape-Morphable and Biodegradable Properties for Stable Brain Signal Monitoring
Neurotechnology•
Effects of repetitive transcranial magnetic stimulation on electroencephalographical measures of poststroke upper limb dysfunction: study protocol for a randomized controlled trial
Neurotechnology•
Distance-based temporal similarity metrics for adaptive channel selection in multi-modal EEG-fNIRS BCI frameworks
Neurotechnology•
Restoring rapid natural bimanual typing with a neuroprosthesis after paralysis
Neurotechnology•
Enhancing the functionality of soft continuum robots for minimally invasive and endoluminal interventions: a review
Neurotechnology•
Clinic-first sepsis recognition in the ICU: a proteomics-guided, parsimonious model with independent validation
Anesthesiology•
Prognostic value of stress hyperglycemia ratio, hemoglobin glycation index, and glycemic variability for postoperative atrial fibrillation: a machine learning-based prediction model
Anesthesiology•
From prediction to practice: closing the translation gap in artificial intelligence for anesthesia
Anesthesiology•
AI-Based Medical Decision Support: Exploring the Data Gap
Public Health•
Using tree-based ensemble methods to produce a population-based mortality risk score in Ontario, Canada
Public Health•
Multiple Targets and Pathways Non-Monotonically Regulate Lung Squamous Cell Carcinoma Migration in Response to Phthalates
Oncology•
Non-invasive profiling of the tumour microenvironment with spatial ecotypes
Oncology•
Estimate renal cell carcinoma recurrence rates using electronic health records
Urology•
Prediction model for additional procedure requirement in flexible ureterorenoscopy using explainable artificial intelligence
Urology•
DNA methylation biomarkers associated with early gastric cardia carcinogenesis
Oncology•
Moderate Predictive Ability of Machine Learning for Achievement of Minimal Clinically Important Difference for the Pain and Healthy Utility Scores after Hip Arthroscopy: Analysis From the Femoroacetabular Impingement RandomiSed Controlled Trial (FIRST) and Embedded Prospective Cohort
Anesthesiology•
Brief narrative interventions for adults with chronic illness or psychosocial distress: a scoping review protocol
Anesthesiology•
Machine learning for risk stratification in the emergency department (MARS-ED) study protocol for a randomized controlled pilot trial on the implementation of a prediction model based on machine learning technology predicting 31-day mortality in the emergency department
Emergency Medicine•
An Algorithm to Avoid Missed Bowel Injuries in Blunt Abdominal Trauma Patients
Emergency Medicine•
Shifts in emergency physicians' attitudes toward large language model-based documentation: a pre- and post-implementation study
Emergency Medicine•
Comparative feasibility of reasoning and non-reasoning large language models for gynecologic cancer emergency care
Emergency Medicine•
Prediction of Respiratory Decompensation in Patients Receiving Home Mechanical Ventilation: Machine Learning Model Development and Validation Study
Emergency Medicine•
Human vs. artificial intelligence in medical charting: a comparative study in the simulated emergency medicine context
Emergency Medicine•
Unveiling the Impact of Occupational Therapy on Acute Care Outcomes: A Machine Learning Approach
Emergency Medicine•
Economic value of AI-based MRI triage for Parkinson’s disease: a cost-benefit study in South Korea and the United States
Emergency Medicine•
Machine learning improves prediction of pulmonary thromboembolism and reduces unnecessary computed tomography scans in the emergency department
Emergency Medicine•
Evaluating large language models for specialist referral triage in primary care: a quantitative study using otolaryngology scenarios
Emergency Medicine•
Machine learning prediction of hospitalization outcomes in critically Ill emergency department patients transported by ambulance: A Retrospective Single Center Cohort Study
Emergency Medicine•
Quantifying immune dysregulation in pneumonia and sepsis with a parsimonious machine-learning model: a multicohort analysis across care settings and reanalysis of a hydrocortisone randomised controlled trial
Emergency Medicine•
Integrating the interpretable machine learning Score For Emergency Risk Prediction (SERP) with emergency department triage to better predict 30-Day mortality
Emergency Medicine•
Research priorities for improved pandemic and epidemic intelligence
Public Health•
Climate and socioeconomic factors drive heterogeneous dengue risk escalation in the Chinese population
Public Health•
Fully automated, deep learning, cardiac CT-based multimodal network for cardiovascular risk stratification in high-risk perioperative patients
Anesthesiology•
From Static Diagnosis to Dynamic Guidance : Evolution of Artificial Intelligence in Pediatric Neuroimaging
Anesthesiology•
Longitudinal Plasma Proteomics Reveals an Immuno-thrombotic Signature that Predicts Radiation Pneumonitis in Lung Cancer
Oncology•
Artificial intelligence for keratosis characterization and identification of lichenoid lesions in histological samples of oral leukoplakia
Medical Informatics•
Development and Validation of an Interpretable Machine Learning Model for Predicting Distant Metastasis in Tongue Squamous Cell Carcinoma: A Multicentre Study
Anesthesiology•
Beyond One-Size-Fits-All: Precision Mechanical Ventilation in ARDS
Anesthesiology•
Deep-learning time-series anomaly detection of acute kidney injury from creatinine–eGFR trajectories in the ICU
Anesthesiology•
Beyond Human Error: Building Intelligent Resilience for Medication Safety in the ICU
Anesthesiology•
Tech-based Evaluation of Healthcare Quality During the COVID-19 Pandemic
Public Health•
Beyond Human Error: Building Intelligent Resilience for Medication Safety in the ICU
Anesthesiology•
Artificial intelligence-assisted risk prediction of postoperative pulmonary complications in non-small cell lung cancer surgery
Anesthesiology•
Engineering biomarker representations of vital signs data enhances deep learning mortality prediction
Anesthesiology•
Circulating DNA reveals nucleosome occupancy patterns that are associated with nucleosome-DNA affinity and are affected in cancer
Oncology•
VitalDB Arrhythmia Database: An Anesthesiologist-Validated Large- scale Intraoperative Arrhythmia Dataset with Beat and Rhythm Labels
Anesthesiology•
Plan A blocks in regional anaesthesia: a narrative review
Anesthesiology•
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