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Yan B, Cao D, Jiang X, Chen Y, Dai W, Dong F, Huang W, Zhang T, Gao C, Chen Q, Yan Z, Wang Z. FedEYE: A scalable and flexible end-to-end federated learning platform for ophthalmology. Patterns (N Y) 2024; 5:100928. [PMID: 38370128 PMCID: PMC10873155 DOI: 10.1016/j.patter.2024.100928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 10/03/2023] [Accepted: 01/11/2024] [Indexed: 02/20/2024]
Abstract
Data-driven machine learning, as a promising approach, possesses the capability to build high-quality, exact, and robust models from ophthalmic medical data. Ophthalmic medical data, however, presently exist across disparate data silos with privacy limitations, making centralized training challenging. While ophthalmologists may not specialize in machine learning and artificial intelligence (AI), considerable impediments arise in the associated realm of research. To address these issues, we design and develop FedEYE, a scalable and flexible end-to-end ophthalmic federated learning platform. During FedEYE design, we adhere to four fundamental design principles, ensuring that ophthalmologists can effortlessly create independent and federated AI research tasks. Benefiting from the design principles and architecture of FedEYE, it encloses numerous key features, including rich and customizable capabilities, separation of concerns, scalability, and flexible deployment. We also validated the applicability of FedEYE by employing several prevalent neural networks on ophthalmic disease image classification tasks.
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Affiliation(s)
- Bingjie Yan
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
- Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Danmin Cao
- Aier Eye Hospital of Wuhan University, Wuhan, China
| | - Xinlong Jiang
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
- Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yiqiang Chen
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
- Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- Peng Cheng Laboratory, Shenzhen, Guangdong, China
| | - Weiwei Dai
- Institute of Digital Ophthalmology and Visual Science, Changsha Aier Eye Hospital, Hunan, China
- AnHui Aier Eye Hospital, Anhui Medical University, Anhui, China
| | - Fan Dong
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
- Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Wuliang Huang
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
- Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Teng Zhang
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
- Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Chenlong Gao
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
- Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Qian Chen
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
- Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Zhen Yan
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
- Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Zhirui Wang
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
- Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
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