"Private, fair and accurate: Training large-scale, privacy-preserving AI ..."

Soroosh Tayebi Arasteh et al. (2023)

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DOI: 10.48550/ARXIV.2302.01622

access: open

type: Informal or Other Publication

metadata version: 2023-02-13

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  - journals/corr/abs-2302-01622
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  - https://dblp.org/rec/journals/corr/abs-2302-01622
Soroosh Tayebi Arasteh, Alexander Ziller, Christiane Kuhl, Marcus R. Makowski, Sven Nebelung, Rickmer Braren, Daniel Rueckert, Daniel Truhn, Georgios Kaissis:
Private, fair and accurate: Training large-scale, privacy-preserving AI models in radiology. CoRR abs/2302.01622 (2023)

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