Factors and machine learning models for predicting successful discontinuation of continuous renal replacement therapy in critically ill patients with acute kidney injury: a retrospective cohort study based on MIMIC-IV database
- 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
-
Factors and machine learning models for predicting successful discontinuation of continuous renal replacement therapy in critically ill patients with acute kidney injury: a retrospective cohort study based on MIMIC-IV database ; volume:25 ; number:1 ; day:12 ; month:11 ; year:2024 ; pages:1-12 ; date:12.2024
BMC nephrology ; 25, Heft 1 (12.11.2024), 1-12, 12.2024
- Urheber
-
Sheng, Shuyue
Li, Andong
Liu, Xiaobin
Shen, Tuo
Zhou, Wei
Lv, Xingping
Shen, Yezhou
Wang, Chun
Ma, Qimin
Qu, Lihong
Ma, Shaolin
Zhu, Feng
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
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10.1186/s12882-024-03844-z
- URN
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urn:nbn:de:101:1-2501292150384.974814462486
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:21 MESZ
Datenpartner
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Beteiligte
- Sheng, Shuyue
- Li, Andong
- Liu, Xiaobin
- Shen, Tuo
- Zhou, Wei
- Lv, Xingping
- Shen, Yezhou
- Wang, Chun
- Ma, Qimin
- Qu, Lihong
- Ma, Shaolin
- Zhu, Feng
- SpringerLink (Online service)
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