Developing a privacy-preserving deep learning model for glaucoma detection: a multicentre study with federated learning
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
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.