FedEYE: A scalable and flexible end-to-end federated learning platform for ophthalmology.

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 princ

SUBMITTER: Yan B 

PROVIDER: S-EPMC10873155 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature