Deep Machine Learning for Identification of Diabetic Retinopathy in Retinal Fundus Photographs

December 05, 2016 Share this content: An algorithm based on deep machine learning may help identify diabetic retinopathy. Deep machine learning used to evaluate retinal fundus images for evidence of diabetic retinopathy can successfully identify these conditions with high specificity and high sensitivity, according to research published in JAMA.1 Lily Peng, MD, PhD, a researcher at Google Inc. in Mountain View, California, and colleagues used applied deep learning techniques to create an algorithm to automatically detect both diabetic retinopathy and diabetic macular edema in retinal fundus photographs. Automated detection has a number of potential benefits, according to background information in the study,1 including increasing the efficiency and coverage of screening programs, reducing barriers to access, and ultimately improving patient outcomes through early treatment and detection. Using a data set of…


Link to Full Article: Deep Machine Learning for Identification of Diabetic Retinopathy in Retinal Fundus Photographs

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