Artificial intelligence for diabetic retinopathy screening, prediction and management

Area of Science:

• Ophthalmology
• Digital Health
• Artificial Intelligence

Background:

• Diabetic retinopathy is a leading complication of diabetes, with current care often fragmented and resource-intensive.
• There is a critical need for innovative care models that leverage digital technology to address these challenges.

Purpose of the Study:

• To review advancements in artificial intelligence (AI) and tele-ophthalmology for diabetic retinopathy screening.
• To outline the potential of AI in risk stratification and management of diabetic macular edema (DME).

Main Methods:

• Review of current literature on AI and telehealth applications in diabetic retinopathy.
• Summary of AI's role in risk stratification and predicting treatment response for DME.
• Discussion of AI adoption in ophthalmology, accelerated by COVID-19.

Main Results:

• AI and telehealth can improve access, financial sustainability, and coverage of diabetic retinopathy screening.
• AI enables risk stratification for vision-threatening diabetic retinopathy and DME.
• AI can predict patient response to anti-vascular endothelial growth factor therapy for DME.

Conclusions:

• Digital health solutions like AI and telehealth can integrate eye care services and optimize patient flow.
• These technologies improve the efficiency of diabetic retinopathy management.
• AI adoption is crucial for modernizing ophthalmology and addressing care gaps.