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. 2023 Dec 26;32(1):269–281. doi: 10.1055/s-0043-1768731

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IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ )

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited.

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Fig. 2 — Pipeline of the literature review. This review collects relevant papers from the literature from 2018 to 2022, including security and privacy in machine learning for health. The research issues focus on adversarial attacks, defenses, and privacy concerns.