医学
青光眼
深度学习
验光服务
患者隐私
人工智能
眼科
计算机科学
医疗保健
经济
经济增长
作者
An Ran Ran,Xi Wang,Poemen P. Chan,M. Wong,Hunter K.L. Yuen,Nai Man Lam,Noel C. Y. Chan,Wilson W. K. Yip,Alvin L. Young,Hon-Wah Yung,Robert T. Chang,Suria S. Mannil,Yih‐Chung Tham,Ching‐Yu Cheng,Tien Yin Wong,Chi Pui Pang,Pheng‐Ann Heng,Clement C. Tham,Carol Y. Cheung
标识
DOI:10.1136/bjo-2023-324188
摘要
Deep learning (DL) is promising to detect glaucoma. However, patients' privacy and data security are major concerns when pooling all data for model development. We developed a privacy-preserving DL model using the federated learning (FL) paradigm to detect glaucoma from optical coherence tomography (OCT) images.
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