Interpretable machine learning model for predicting acute kidney injury in critically ill patients
- 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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Interpretable machine learning model for predicting acute kidney injury in critically ill patients ; volume:24 ; number:1 ; day:31 ; month:5 ; year:2024 ; pages:1-12 ; date:12.2024
BMC medical informatics and decision making ; 24, Heft 1 (31.5.2024), 1-12, 12.2024
- Urheber
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Li, Xunliang
Wang, Peng
Zhu, Yuke
Zhao, Wenman
Pan, Haifeng
Wang, Deguang
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
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10.1186/s12911-024-02537-9
- URN
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urn:nbn:de:101:1-2408082106546.967932751161
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:48 MESZ
Datenpartner
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Beteiligte
- Li, Xunliang
- Wang, Peng
- Zhu, Yuke
- Zhao, Wenman
- Pan, Haifeng
- Wang, Deguang
- SpringerLink (Online service)
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