Medical Federated Learning Alliance to Build a Precision Health Industry
Federated learning is a key approach to the transformation of the core strategic industry of precision health
Medical federated learning highlights case
Wu Mingxian, President of National Taiwan University Hospital and Chen Shian, President of Taiwan Zhongrong, explained the highlights of joint learning in a special interview. Wu Mingxian: Asian medical care, let Taiwan write a guest editor in chief with science and democracy – Future City @ World (2021.3)
Medical federated learning 5G The result of AIoT industrial solutions
Media report
遠見雜誌: “federated Learning” has given birth to 120 most powerful medical brains
天下雜誌: “federated Learning” Breaks Data Barriers
中央通訊社: AI detection X-ray film covid-19 approved by the food and drug department for the first time
蘋果日報: [hold the hospital] the accuracy rate is 90%! Zero contact diagnosis by AI wufei Beiyi catches Russian ballet dancers infected with epidemic disease
Digitimes: Federated learning to break hospital boundaries, lung infiltration, cardiology
iThome: Centralized health care big data strengthens the interpretation of heterogeneous images by brain tumor AI. Taipei Rongzong is more independent in Taiwan and uses joint learning to break the bottleneck of medical AI big data
iThome: [the first joint learning experiment of local hospitals in Taiwan] Taipei Rongzong relies on supercomputers to verify the feasibility and make the local AI have the strength of the International Cup