Artificial intelligence-based apps for screening and diagnosing diabetic retinopathy and common ocular disorders

Abstract

Artificial intelligence (AI), encompassing machine learning and deep learning, is being extensively used in medical sciences. It is slated to positively impact the diagnosis and prognostication of various diseases. Deep learning, a subset of AI, has been instrumental in diagnosing diabetic retinopathy (DR), diabetic macular edema, glaucoma, age-related macular degeneration, and numerous other ocular diseases. AI performs equally well in the early prediction of glaucoma and age-related macular degeneration. Integrating AI with telemedicine promises to improve healthcare delivery, although challenges persist in implementing AI algorithms, especially in developing countries. This review provides a comprehensive summary of AI, its applications in ophthalmology, particularly DR, the diverse algorithms utilized for different ocular conditions, and prospects for the future integration of AI in eye care.

Keywords: Age-related macular degeneration; Alzheimer's disease; Artificial intelligence; Automatic retinal image analysis; Chronic kidney disease; Convolutional neural networks; Diabetic retinopathy; Diabetic macular edema; International council of ophthalmology; Machine learning; Massive training artificial neural networks; Natural language processing; OCT angiography; Optical coherence tomography; Vision transformers

Core Tip: In this modern world, artificial intelligence-based algorithms have a definitive role in the early screening of different ocular diseases. Early screening helps in rapid referral and appropriate management to prevent sight-threatening complications. However, all said and done, it needs to be applied wisely to preserve the importance of human touch and empathy in clinical practice.