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Tayebi Arasteh, Soroosh https://orcid.org/0000-0003-1015-7733

Ziller, Alexander https://orcid.org/0000-0002-3242-0195

Kuhl, Christiane

Makowski, Marcus https://orcid.org/0000-0001-8778-647X

Nebelung, Sven https://orcid.org/0000-0002-5267-9962

Braren, Rickmer https://orcid.org/0000-0001-6039-6957

Rueckert, Daniel https://orcid.org/0000-0002-5683-5889

Truhn, Daniel https://orcid.org/0000-0002-9605-0728

Kaissis, Georgios https://orcid.org/0000-0001-8382-8062

Funding for this research was provided by:

Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie (01ZZ2316C)

The Bavarian State Ministry for Science and the Arts through the Munich Centre for Machine Learning.

Bundesministerium für Bildung und Forschung (01KX2021)

Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie (01ZZ2316C)

Deutsches Konsortium für Translationale Krebsforschung

The Bavarian State Ministry for Science and the Arts through the Munich Centre for Machine Learning. ERC Grant Deep4MI

Bundesministerium für Bildung und Forschung (01KD2215B)

EC | Horizon 2020 Framework Programme (101057091)

Text and Data Mining valid from 2024-03-14

Version of Record valid from 2024-03-14