Deep-Learning Algorithm Shows Promise in Diabetic Eyes

Action Points An algorithm based on deep machine learning demonstrated high sensitivity and specificity for detecting referable diabetic retinopathy. Note that additional studies are needed to further validate the algorithm, specifically to compare severe diabetic retinopathy to referable diabetic retinopathy. An algorithm based on deep machine learning demonstrated high sensitivity and specificity for detecting referable diabetic retinopathy, researchers reported. In two validation sets (EyePACS-1 and Messidor-2) at the operating point selected for high specificity, the algorithm had 90.3% and 87% sensitivity, and 98.1% and 98.5% specificity, for detecting referable diabetic retinopathy, which was defined as moderate or worse diabetic retinopathy or referable macular edema, according to Varun Gulshan, PhD, of Google Inc. in Mountain View, Calif., and colleagues. The EyePACS-1 algorithm had a receiver operating curve (ROC) of 0.991 (95%…


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