首页|Data on Machine Learning Reported by Danmin Cao and Colleagues (FedEYE: A scalab le and flexible end-to-end federated learning platform for ophthalmology)
Data on Machine Learning Reported by Danmin Cao and Colleagues (FedEYE: A scalab le and flexible end-to-end federated learning platform for ophthalmology)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting originating in Wuhan, People' s Republic of China, by NewsRx journalists, research stated, "Datadriven machin e learning, as a promising approach, possesses the capability to build high-qual ity, exact, and robust models from ophthalmic medical data. Ophthalmic medical d ata, however, presently exist across disparate data silos with privacy limitatio ns, making centralized training challenging." The news reporters obtained a quote from the research, "While ophthalmologists m ay not specialize in machine learning and artificial intelligence (AI), consider able impediments arise in the associated realm of research. To address these iss ues, we design and develop FedEYE, a scalable and flexible end-to-end ophthalmic federated learning platform. During FedEYE design, we adhere to four fundamenta l design principles, ensuring that ophthalmologists can effortlessly create inde pendent and federated AI research tasks. Benefiting from the design principles a nd architecture of FedEYE, it encloses numerous key features, including rich and customizable capabilities, separation of concerns, scalability, and flexible de ployment." According to the news reporters, the research concluded: "We also validated the applicability of FedEYE by employing several prevalent neural networks on ophtha lmic disease image classification tasks." For more information on this research see: FedEYE: A scalable and flexible end-t o-end federated learning platform for ophthalmology. Patterns, 2024;5(2):100928.
WuhanPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesHealth and MedicineMachine LearningOphthalm ology
NETL
NSTL
