ArticleScientific reports2026
Diagnostic performance of an artificial intelligence software for diabetic retinopathy organised screening in a pilot study.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Diabetic retinopathy (DR) is one of the most common complications of diabetes mellitus (DM) with a prevalence that varies from 10% to 61% in different countries. From healthcare to the precise prevention, diagnosis, and management of diseases, Artificial Intelligence (AI) is progressing rapidly in interdisciplinary fields, including ophthalmology. We aimed to explore the efficacy of artificial intelligence (AI)-based screening for diabetic retinopathy in type 2 DM patients. High-resolution colour fundus photographs were obtained for all patients using a non-mydriatic camera (Nidek AFC-330). DAIRET software uses a machine learning algorithm to identify the most important signs of DR. The software provides an output with a binary result: negative, in case of no referable disease or positive, when the presence of signs of DR is detected. The photographs were also manually graded negative or positive for DR by an expert ophthalmologist, masked to AI responses. Expert clinical opinion was used as the reference (gold standard), and the results were compared with those of the AI responses. A significant association was observed between DAIRET and expert diagnosis (χ
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