Abstract
Rates of diabetic retinopathy (DR) and diabetic macular edema (DME), a common ocular complication of diabetes mellitus, are increasing worldwide. There is a substantial burden concerning the detection and management of this condition, particularly in low-resource settings, due to limitations such as the time, cost, and labor associated with current screening and treatment methods. Artificial intelligence (AI) is a modality of pattern recognition that has the potential to combat these limitations in a reliable and cost-effective way. This review explores the various applications of AI on the screening, management, and treatment of DR and DME. AI applications for detecting referable DR and DME have been the most thoroughly researched applications for this condition. While some studies exist using AI to stratify DR patients based on the risk of progression, predict treatment outcomes to anti-VEGF therapy, and explore the utilization of AI for clinical trials to develop new treatments for DR, further validation studies on larger datasets are warranted.