Preserving fairness and diagnostic accuracy in private large-scale AI models for medical imaging
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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1 Online-Ressource.
- Sprache
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Englisch
- Erschienen in
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Preserving fairness and diagnostic accuracy in private large-scale AI models for medical imaging ; volume:4 ; number:1 ; day:14 ; month:3 ; year:2024 ; pages:1-12 ; date:12.2024
Communications medicine ; 4, Heft 1 (14.3.2024), 1-12, 12.2024
- Urheber
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Tayebi Arasteh, Soroosh
Ziller, Alexander
Kuhl, Christiane
Makowski, Marcus
Nebelung, Sven
Braren, Rickmer
Rueckert, Daniel
Truhn, Daniel
Kaissis, Georgios
- Beteiligte Personen und Organisationen
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SpringerLink (Online service)
- DOI
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10.1038/s43856-024-00462-6
- URN
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urn:nbn:de:101:1-2405162103071.546116477274
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 11:02 MESZ
Datenpartner
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Beteiligte
- Tayebi Arasteh, Soroosh
- Ziller, Alexander
- Kuhl, Christiane
- Makowski, Marcus
- Nebelung, Sven
- Braren, Rickmer
- Rueckert, Daniel
- Truhn, Daniel
- Kaissis, Georgios
- SpringerLink (Online service)
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