Less is more: Detecting clinical deterioration in the hospital with machine learning using only age, heart rate, and respiratory rate

Author:

Akel M.A.,Carey K.A.,Winslow C.J.,Churpek M.M.,Edelson D.P.

Funder

U.S. Department of Defense

National Institute of General Medical Sciences

Publisher

Elsevier BV

Subject

Cardiology and Cardiovascular Medicine,Emergency,Emergency Medicine

Reference9 articles.

1. Risk stratification of hospitalized patients on the wards;Churpek;Chest,2013

2. Validation of a modified Early Warning Score in medical admissions;Subbe;QJM,2001

3. Multicenter development and validation of a risk stratification tool for ward patients;Churpek;Am J Respir Crit Care Med,2014

4. Multicenter comparison of machine learning methods and conventional regression for predicting clinical deterioration on the wards;Churpek;Crit Care Med,2016

5. Accuracy comparisons between manual and automated respiratory rate for detecting clinical deterioration in ward patients;Churpek;Under Rev J Hosp Med,2017

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