Multicenter validation of a machine-learning algorithm for 48-h all-cause mortality prediction

In order to evaluate mortality predictions based on boosted trees, this retrospective study uses electronic medical record data from three academic health centers for inpatients 18 years or older with at least one observation of each vital sign. Predictions were made 12, 24, and 48 hours before deat...

Ausführliche Beschreibung

Bibliografische Detailangaben

Hauptverfasser:	Hamid Mohamadlou, Saarang Panchavati, Jacob Calvert, Anna Lynn-Palevsky, Sidney Le, Angier Allen, Emily Pellegrini, Abigail Green-Saxena, Christopher Barton, Grant Fletcher, Lisa Shieh, Philip B Stark, Uli Chettipally, David Shimabukuro, Mitchell Feldman, Ritankar Das
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	SAGE Publishing 2020-09-01
Schriftenreihe:	Health Informatics Journal
Online-Zugang:	https://doi.org/10.1177/1460458219894494
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