Assessment of Artificial Intelligence software for automatic screening of Diabetic Retinopathy based on fundus photographs in Melanoderm subjects.


Journal

Retina (Philadelphia, Pa.)
ISSN: 1539-2864
Titre abrégé: Retina
Pays: United States
ID NLM: 8309919

Informations de publication

Date de publication:
15 Oct 2024
Historique:
medline: 22 10 2024
pubmed: 22 10 2024
entrez: 22 10 2024
Statut: aheadofprint

Résumé

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's. The clinical results were compared to 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 (AUC) 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 AUC 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 AUC of 0.988. Considering these results, we may conclude that Gaiha Prio Retino +™ is an effective tool for screening referable DR.

Identifiants

pubmed: 39437373
doi: 10.1097/IAE.0000000000004310
pii: 00006982-990000000-00828
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Classifications MeSH