Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study

Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study

Abstract Data privacy mechanisms are essential for rapidly scaling medical training databases to capture the heterogeneity of patient data distributions toward robust and generalizable machine learning systems. In the current COVID-19 pandemic, a major focus of artificial intelligence (AI) is interp...

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Auteurs principaux: Qi Dou, Tiffany Y. So, Meirui Jiang, Quande Liu, Varut Vardhanabhuti, Georgios Kaissis, Zeju Li, Weixin Si, Heather H. C. Lee, Kevin Yu, Zuxin Feng, Li Dong, Egon Burian, Friederike Jungmann, Rickmer Braren, Marcus Makowski, Bernhard Kainz, Daniel Rueckert, Ben Glocker, Simon C. H. Yu, Pheng Ann Heng
Format: article
Langue:EN
Publié: Nature Portfolio 2021
Sujets:
Computer applications to medicine. Medical informatics
R858-859.7
Accès en ligne:https://doaj.org/article/340f463aed8748e1b87b2603e67e7d80
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https://doaj.org/article/340f463aed8748e1b87b2603e67e7d80

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