Comprehensive Summary
This article showcases a new digital health system that is designed to build trust between patients and technology. It describes a trust aware framework that personalizes care by combining user modeling, reasoning, and adaptive trust features. The system creates detailed patient profiles called blueprint personas that include clinical, behavioral, and emotional information. Using these profiles, an intelligent agent communicates with patients and healthcare providers in a way that feels more personal and supportive. An ontology based reasoning layer helps the system interpret data from medical records, wearable devices, and environmental sources to meet patient needs. A formal trust model allows the system to adjust how it communicates depending on the user’s feedback and level of trust. A test example with a patient who has chronic lung disease shows how the system can give reminders and air quality alerts. Although it has not yet been tested in real hospitals, it is built to be flexible and easy to expand. The article suggests that combining personalization and trust can help make AI based healthcare systems more effective and patient friendly.
Outcomes and Implications
This study shows how digital health systems can be improved by focusing on trust and personalization. With technology that understands emotions and behavior, doctors can offer care that goes beyond their current capacity. For people with chronic illnesses, these systems will remind them to take medicine, notice environmental triggers, and support their daily routines. A trust aware system might also make patients feel more comfortable and involved in their care. However, this system needs testing in real medical settings to prove its safety and accuracy. Doctors will also need training to understand how to use the technology responsibly. A system of this type can improve patient outcomes and build stronger connections between patients and digital healthcare tools.