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Report: State of the Art Solutions for Privacy Preserving Machine
  Learning in the Medical Context

Report: State of the Art Solutions for Privacy Preserving Machine Learning in the Medical Context

27 January 2022
J. Zalonis
Frederik Armknecht
Björn Grohmann
Manuel Koch
ArXivPDFHTML

Papers citing "Report: State of the Art Solutions for Privacy Preserving Machine Learning in the Medical Context"

2 / 2 papers shown
Title
Privacy-preserving machine learning for healthcare: open challenges and
  future perspectives
Privacy-preserving machine learning for healthcare: open challenges and future perspectives
Alejandro Guerra-Manzanares
L. J. L. Lopez
Michail Maniatakos
Farah E. Shamout
15
9
0
27 Mar 2023
Non-readily identifiable data collaboration analysis for multiple
  datasets including personal information
Non-readily identifiable data collaboration analysis for multiple datasets including personal information
A. Imakura
T. Sakurai
Yukihiko Okada
Tomoya Fujii
Teppei Sakamoto
Hiroyuki Abe
FedML
17
10
0
31 Aug 2022
1