Abstract
Summary: This prospective observational study evaluated the performance of a diabetic retinopathy diagnostic system (IDx-DR) compared to the gold standard diagnostic for diabetic retinopathy. Nine hundred individuals with diabetes but without a history of diabetic retinopathy were examined. Retinal images of the patients were obtained using a robotic camera, and a clinical diagnosis was made in 20 seconds by an artificial intelligence (AI) diagnostic system and compared to images read by three experienced and validated readers. The AI system correctly identified 173 of the 198 individuals with more than mild diabetic retinopathy, (a sensitivity of 87%), and 556 of the 621 disease-free individuals (a specificity of 90%).
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