Data Sheet 1_Clinical validation of artificial intelligence algorithms for the detection of different central-involved retinal pathologies and glaucoma from non-mydriatic images.docx
Version 1The use of Artificial intelligence (AI) algorithms for detecting different ophthalmic diseases, especially diabetic retinopathy (DR), has become increasingly popular. In this paper, we evaluate the screening performance of different AI algorithms based on convolutional neural networks (CNNs) in a real-world scenario. To that aim, we conducted an observational and cross-sectional study on patients aged ≥18 years with type-2 diabetes mellitus, who had undergone fundus examination for DR screening
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The use of Artificial intelligence (AI) algorithms for detecting different ophthalmic diseases, especially diabetic retinopathy (DR), has become increasingly popular. In this paper, we evaluate the screening performance of different AI algorithms based on convolutional neural networks (CNNs) in a real-world scenario. To that aim, we conducted an observational and cross-sectional study on patients aged ≥18 years with type-2 diabetes mellitus, who had undergone fundus examination for DR screening