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

Ethics, Privacy, and Legal Issues (411) Mobile Health (mhealth) (2365) Digital Health Reviews (999) Data Science (163) Clinical Informatics (706) E-Health Policy and Health Systems Innovation (166) Policy and Policy Proposals (95)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41588, first published .
Federated Machine Learning, Privacy-Enhancing Technologies, and Data Protection Laws in Medical Research: Scoping Review

Federated Machine Learning, Privacy-Enhancing Technologies, and Data Protection Laws in Medical Research: Scoping Review

Federated Machine Learning, Privacy-Enhancing Technologies, and Data Protection Laws in Medical Research: Scoping Review

Authors of this article:

Alissa Brauneck 1 Author Orcid Image ;   Louisa Schmalhorst 1 Author Orcid Image ;   Mohammad Mahdi Kazemi Majdabadi 2 Author Orcid Image ;   Mohammad Bakhtiari 2 Author Orcid Image ;   Uwe Völker 3 Author Orcid Image ;   Jan Baumbach 2, 4 Author Orcid Image ;   Linda Baumbach 5 Author Orcid Image ;   Gabriele Buchholtz 1 Author Orcid Image
Article Authors Cited by (9) Tweetations (4) Metrics

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  4. Pelc M, Vilimkova Kahankova R, Blaszczyszyn M, Mikolajewski D, Konieczny M, Khoma V, Bara G, Zygarlicki J, Martinek R, Gupta M, Gorzelanczyk E, Pawłowski M, Czapiga B, Zygarlicka M, Kawala-Sterniuk A. Initial study on an expert system for spine diseases screening using inertial measurement unit. Scientific Reports 2023;13(1) View
  5. Guan B, Yu L, Li Y, Jia Z, Jin Z. Assessment of patients with Parkinson’s disease based on federated learning. International Journal of Machine Learning and Cybernetics 2023 View
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