This paper is in the following e-collection/theme issue:

Artificial Intelligence (1754) Clinical Information and Decision Making (1665) New Methods (1032) Machine Learning (1748)

Published on in Vol 22, No 10 (2020): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/20891, first published .
Federated Learning on Clinical Benchmark Data: Performance Assessment

Federated Learning on Clinical Benchmark Data: Performance Assessment

Federated Learning on Clinical Benchmark Data: Performance Assessment

Authors of this article:

Geun Hyeong Lee1 Author Orcid Image ;   Soo-Yong Shin1, 2, 3 Author Orcid Image
Article Authors Cited by (88) Tweetations (7) Metrics
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Sven Awege Sven Awege @SVENNIECO

Federated Learning on Clinical Benchmark Data: Performance Assessment https://t.co/GkeYYD0s2u

2:37 PM · Oct 26, 2020

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JMIR Publications JMIR Publications @jmirpub

New in JMIR: Federated Learning on Clinical Benchmark Data: Performance Assessment https://t.co/pUNKnytfpL https://t.co/lAfIhrOZ3w

2:55 PM · Oct 26, 2020

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fredbarney fredbarney @yabbadabbadoo99

Federated Learning on Clinical Benchmark Data: Performance Assessment https://t.co/WI3sgRpx6R

3:07 PM · Oct 26, 2020

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Nate DiNiro Nate DiNiro @unclenate

Towards a 'Learning' Health System https://t.co/x8OsqcdhF6

11:03 PM · Oct 26, 2020

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Vince Kuraitis Vince Kuraitis @VinceKuraitis

Samsung study: "Federated Learning (FL) can achieve high performance while maintaining privacy protection because… https://t.co/JE0ymNuU45

11:08 PM · Oct 26, 2020

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Axiomedix_PM Axiomedix_PM @axiomedix

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6:06 PM · Dec 02, 2020

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Australian Adventure Australian Adventure @AdventAustralia

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4:07 AM · Dec 12, 2020

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