ASSESSMENT OF ARTIFICIAL INTELLIGENCE SOFTWARE FOR AUTOMATIC SCREENING OF DIABETIC RETINOPATHY BASED ON FUNDUS PHOTOGRAPHS IN MELANODERM SUBJECTS

• Published in: Retina (Philadelphia, Pa.) Vol. 45; no. 2; p. 330
• Main Authors: Mbaye, Soda, Aw, Aïssatou, Sy, El Hadji Malick, Ka, Aly Mbara, Diagne, Jean Pierre, Diallo, Hawo Madina, Samra, Audrey, Ndiaye, Papa Amadou
• Format: Journal Article
• Language: English
• Published: United States 01.02.2025
• Subjects: Adult; Aged; Artificial Intelligence; Diabetic Retinopathy - diagnosis; Female; Fundus Oculi; Humans; Male; Middle Aged; Photography - methods; Prospective Studies; ROC Curve; Sensitivity and Specificity; Software
• ISSN: 1539-2864
• DOI: 10.1097/IAE.0000000000004310

To assess the Gaiha Prio Retino +™ Artificial Intelligence (AI) software for detecting diabetic retinopathy (DR). This prospective study was conducted from March 1, 2021, to September 30, 2022, in the Ophthalmology Department of the Abass NDAO Hospital (Dakar, Senegal). The clinical classification of DR was based on American Academy of Ophthalmology. The clinical results were compared with those obtained from the automated reading of retinophotos taken using Gaiha Prio Retino +™, a software designed to detect DR. The study covered 305 eyes. Referable DR was observed in 104 eyes by the ophthalmologist and in 96 eyes by AI, corresponding with a sensitivity of 92.31%, a specificity of 99%, and an area under the curve of 0.989. Vision-threatening DR was detected in 102 eyes by the ophthalmologist and in 94 eyes by AI, with a corresponding sensitivity of 92.16%, specificity of 99.01%, and an area under the curve of 0.975. Maculopathy was identified in 93 eyes by the ophthalmologist and in 89 eyes by AI, with a corresponding sensitivity of 95.7%, specificity of 97.17%, and an area under the curve of 0.988. Considering these results, the authors may conclude that Gaiha Prio Retino +™ is an effective tool for screening referable DR.