Application of deep learning image assessment software VeriSee™ for diabetic retinopathy screening

• Published in: Journal of the Formosan Medical Association Vol. 120; no. 1; pp. 165 - 171
• Main Authors: Hsieh, Yi-Ting, Chuang, Lee-Ming, Jiang, Yi-Der, Chang, Tien-Jyun, Yang, Chung-May, Yang, Chang-Hao, Chan, Li-Wei, Kao, Tzu-Yun, Chen, Ta-Ching, Lin, Hsuan-Chieh, Tsai, Chin-Han, Chen, Mingke
• Format: Journal Article
• Language: English
• Published: Singapore Elsevier B.V 01.01.2021; Elsevier
• Subjects: Artificial intelligence; Convolutional neural network; Deep Learning; Diabetic retinopathy; Diabetic Retinopathy - diagnostic imaging; Humans; Mass Screening; Photography; Retinal fundus photography; Retrospective Studies; Software; Taiwan; Taiwan; Deep learning; Diabetic retinopathy; Retinal fundus photography; Artificial intelligence; Convolutional neural network

To develop a deep learning image assessment software VeriSee™ and to validate its accuracy in grading the severity of diabetic retinopathy (DR). Diabetic patients who underwent single-field, nonmydriatic, 45-degree color retinal fundus photography at National Taiwan University Hospital between July...