Artificial Intelligence Systems for Diabetic Retinopathy Screening: Appraisal on the 3rd US FDA Approved Algorithms- AEYE-DS

Abstract

Artificial Intelligence (AI) has revolutionized the field of healthcare in recent years, and one of its most promising applications is on the interpretation of medical images [1]. In ophthalmology, the first success comes to the screening and diagnosis of Diabetic Retinopathy (DR) [2]. DR is a common complication of Diabetes Mellitus (DM) that affects the eyes, and early detection and treatment is crucial in preventing vision loss, especially over the working populations [3]. The use of AI in DR screening involves analyzing digital fundus images to detect any signs of DR, including microaneurysms, dot and blot haemorrhages, cotton-wool spots, venous beading, intraretinal microvascular anomalies [4]. Currently, there are 3 US FDA approved systems on DR screening, IDx-DR (Digital Diagnostics), EyeArt (Eyenuk, Inc) and AEYE-DS (AEYE Health, Inc) [5-7]. AI has several advantages over traditional screening methods, including usage by non-ophthalmologically trained medical personnel, accessible and stable performance over whatever time and place, increased speed of clinical workflow, these might potentially help to improve outcomes for patients with DM. In the era of rapidly advancing technology, the use of AI in ophthalmology is an exciting development that might transform our future practice [8]. In this appraisal, we focus on the 3rd US FDA approved AI algorithms for DR.