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Use in clinical practice of an automated screening method of diabetic retinopathy that can be derived using a diagnostic artificial intelligence syst…
2020
Abstract Background and Objective To compare the diagnostic performance of an autonomous diagnostic artificial intelligence (AI) system for the diagnosis of derivable diabetic retinopathy (RDR) with manual classification. Materials and Methods Patients with type 1 and type 2 diabetes participated in a diabetic retinopathy (RD) screening program between 2011–2012. 2 images of each eye were collected. Unidentifiable retinal images were obtained, one centered on the disc and one on the fovea. The exams were classified with th e autonomous AI system and manually by anonymous ophthalmologists. The results of the AI system and manual classification were compared in terms of sensitivity and specif…