Revolutionizing Diabetic Retinopathy Detection: A Comprehensive Review of AI Approaches

Diabetes presents a global challenge to eye health due to its increasing prevalence and aging population. Detecting diabetic retinopathy (DR) in these patients is a significant hurdle. Various groups have turned to artificial intelligence (AI) with machine learning and deep learning to create automated DR detection algorithms. This article aims to explore cutting-edge AI technologies for DR screening found in the literature, some of which are already in the commercial market. These technologies were developed using diverse training datasets and technical approaches. While many groups have reported strong diagnostic performance for AI-based DR screening, future research must address various challenges, such as legal and ethical considerations, as well as clinical deployment models, to facilitate the integration of these innovative technologies into healthcare settings.