A machine-learning approach to human ex vivo lung perfusion predicts transplantation outcomes and promotes organ utilization
- 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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A machine-learning approach to human ex vivo lung perfusion predicts transplantation outcomes and promotes organ utilization ; volume:14 ; number:1 ; day:9 ; month:8 ; year:2023 ; pages:1-8 ; date:12.2023
Nature Communications ; 14, Heft 1 (9.8.2023), 1-8, 12.2023
- Urheber
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Sage, Andrew T.
Donahoe, Laura L.
Shamandy, Alaa A.
Mousavi, S. Hossein
Chao, Bonnie T.
Zhou, Xuanzi
Valero, Jerome
Balachandran, Sharaniyaa
Ali, Aadil
Martinu, Tereza
Tomlinson, George
Sorbo, Lorenzo Del
Yeung, Jonathan C.
Liu, Mingyao
Cypel, Marcelo
Wang, Bo
Keshavjee, Shaf
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1038/s41467-023-40468-7
- URN
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urn:nbn:de:101:1-2024020210441815180208
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
- 15.08.2025, 07:24 MESZ
Datenpartner
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Beteiligte
- Sage, Andrew T.
- Donahoe, Laura L.
- Shamandy, Alaa A.
- Mousavi, S. Hossein
- Chao, Bonnie T.
- Zhou, Xuanzi
- Valero, Jerome
- Balachandran, Sharaniyaa
- Ali, Aadil
- Martinu, Tereza
- Tomlinson, George
- Sorbo, Lorenzo Del
- Yeung, Jonathan C.
- Liu, Mingyao
- Cypel, Marcelo
- Wang, Bo
- Keshavjee, Shaf
- SpringerLink (Online service)
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