The future of digital health with federated learning.
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ABSTRACT:
SUBMITTER: Rieke N
PROVIDER: S-EPMC7490367 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
Publications
The future of digital health with federated learning.
Rieke Nicola N Hancox Jonny J Li Wenqi W Milletarì Fausto F Roth Holger R HR Albarqouni Shadi S Bakas Spyridon S Galtier Mathieu N MN Landman Bennett A BA Maier-Hein Klaus K Ourselin Sébastien S Sheller Micah M Summers Ronald M RM Trask Andrew A Xu Daguang D Baust Maximilian M Cardoso M Jorge MJ
NPJ digital medicine 20200914
Data-driven machine learning (ML) has emerged as a promising approach for building accurate and robust statistical models from medical data, which is collected in huge volumes by modern healthcare systems. Existing medical data is not fully exploited by ML primarily because it sits in data silos and privacy concerns restrict access to this data. However, without access to sufficient data, ML will be prevented from reaching its full potential and, ultimately, from making the transition from resea ...[more]
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