Internal and External Validation of a Machine Learning Risk Score for Acute Kidney Injury

IMPORTANCE: Acute kidney injury (AKI) is associated with increased morbidity and mortality in hospitalized patients. Current methods to identify patients at high risk of AKI are limited, and few prediction models have been externally validated. OBJECTIVE: To internally and externally validate a mach...

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Vydané v:	JAMA Network Open Ročník 3; číslo 8; s. e2012892
Hlavní autori:	Churpek, Matthew M, Carey, Kyle A, Edelson, Dana P, Singh, Tripti, Astor, Brad C, Gilbert, Emily R, Winslow, Christopher, Shah, Nirav, Afshar, Majid, Koyner, Jay L
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States American Medical Association 11.08.2020
Predmet:	Acute Kidney Injury - diagnosis Acute Kidney Injury - epidemiology Adult Aged Aged, 80 and over Female Humans Kidney diseases Machine Learning Male Middle Aged Models, Statistical Nephrology Online Only Original Investigation Retrospective Studies Risk Assessment - methods Risk Factors ROC Curve
ISSN:	2574-3805, 2574-3805
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