GOOGLE ARDA TOOL USING ARTIFICIAL INTELLIGENCE IN SELF-OPTIMIZING ALGORITHM TO PREVENT DIABETIC RETINOPATHY AND DIABETIC MACULAR EDOEMA (DME)

Abstract

Diabetic retinopathy is an aspect of diabetes which produces vascular abnormalities that might result in blindness. Since the symptoms with this illness are lasting, detection at an early stage is crucial because untreated eye disease may lead to blindness. The detection of microaneurysms using digital color fundus images is an essential initial step in automated diabetic retinopathy testing. Manually diagnosis (by physicians) for such ailment requires time and is vulnerable to inaccuracy. There have been several computer vision-based algorithms created for autonomously recognizing Diabetic Retinopathy. In this study on Automated Retinal Disease Assessment, or ARDA, employs artificial intelligence to aid healthcare professionals in detecting diabetic retinopathy, providing the potential for AI algorithms to assist physicians in diagnosing additional illnesses in future research.