Tayebi Arasteh, Soroosh http://orcid.org/0000-0003-1015-7733
Ziller, Alexander http://orcid.org/0000-0002-3242-0195
Kuhl, Christiane
Makowski, Marcus http://orcid.org/0000-0001-8778-647X
Nebelung, Sven http://orcid.org/0000-0002-5267-9962
Braren, Rickmer http://orcid.org/0000-0001-6039-6957
Rueckert, Daniel http://orcid.org/0000-0002-5683-5889
Truhn, Daniel http://orcid.org/0000-0002-9605-0728
Kaissis, Georgios http://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)
Article History
Received: 6 April 2023
Accepted: 16 February 2024
First Online: 14 March 2024
Competing interests
: The authors declare no competing interests.