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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Vydané v:	Critical care medicine Ročník 44; číslo 2; s. 368 - 374
Hlavní autori:	Churpek, Matthew M, Yuen, Trevor C, Winslow, Christopher, Meltzer, David O, Kattan, Michael W, Edelson, Dana P
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 01.02.2016
Predmet:	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
On-line prístup:	Zistit podrobnosti o prístupe
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