Comprehensive Summary
This review explores the rapidly expanding role of artificial intelligence (AI) in the field of ophthalmology, particularly in diagnosing, monitoring, and treating eye diseases. The authors conducted a comprehensive literature search of approximately 400 articles from January 2016 to June 2020 using PubMed and Google Scholar. The study highlights the effectiveness of AI systems, especially convolutional neural networks (CNNs), in achieving expert-level performance in classifying diabetic retinopathy (DR) and age-related macular degeneration (AMD) and interpreting optical coherence tomography (OCT) images. Notably, commercial tools like IDx-DR and EyRIS SELENA+ have received regulatory approval for DR screening. The review underscores AI's potential to enhance healthcare sustainability by streamlining screening, staging, and treatment planning, thereby reducing the workload of specialists. The authors predict a significant transformation in ophthalmology within the next two to five years due to the global adoption of AI technologies.
Outcomes and Implications
The research is crucial given the aging population and rising diabetes incidence, which are increasing the prevalence of conditions like age-related macular degeneration and diabetic retinopathy. This places a heavy burden on global healthcare systems, especially in low- and middle-income countries where specialists are scarce. AI-based systems offer a cost-effective solution for universal screening and early treatment, potentially leading to earlier detection and referral, personalized treatment guidelines, and improved patient adherence. The authors foresee a profound transformation in ophthalmology, with AI systems enabling significant improvements in patient management and healthcare delivery.