Multicenter Comparison of Machine Learning Methods and Conventional Regression for Predicting Clinical Deterioration on the Wards

Machine learning methods are flexible prediction algorithms that may be more accurate than conventional regression. We compared the accuracy of different techniques for detecting clinical deterioration on the wards in a large, multicenter database. Observational cohort study. Five hospitals, from No...

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Bibliographic Details
Published in:	Critical care medicine Vol. 44; no. 2; pp. 368 - 374
Main Authors:	Churpek, Matthew M, Yuen, Trevor C, Winslow, Christopher, Meltzer, David O, Kattan, Michael W, Edelson, Dana P
Format:	Journal Article
Language:	English
Published:	United States 01.02.2016
Subjects:	Age Factors Cohort Studies Diagnostic Techniques and Procedures Heart Arrest - mortality Humans Intensive Care Units - organization & administration Logistic Models Machine Learning - utilization Models, Statistical Neural Networks (Computer) Risk Assessment ROC Curve Socioeconomic Factors Support Vector Machine Survival Analysis Time Factors Vital Signs
ISSN:	1530-0293
Online Access:	Get more information
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