Predicting individual physiologically acceptable states at discharge from a pediatric intensive care unit

Quantify physiologically acceptable PICU-discharge vital signs and develop machine learning models to predict these values for individual patients throughout their PICU episode. EMR data from 7256 survivor PICU episodes (5632 patients) collected between 2009 and 2017 at Children's Hospital Los...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Journal of the American Medical Informatics Association : JAMIA 2018-12, Vol.25 (12), p.1600-1607
Hauptverfasser:	Carlin, Cameron S, Ho, Long V, Ledbetter, David R, Aczon, Melissa D, Wetzel, Randall C
Format:	Artikel
Sprache:	eng
Schlagworte:	Research and Applications
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!