Early Prediction of Acute Kidney Injury in the Emergency Department With Machine-Learning Methods Applied to Electronic Health Record Data-Reference-Cited by-同舟云学术

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Early Prediction of Acute Kidney Injury in the Emergency Department With Machine-Learning Methods Applied to Electronic Health Record Data

Published:2020-10 Issue:4 Volume:76 Page:501-514
ISSN:0196-0644
Container-title:Annals of Emergency Medicine
language:en
Short-container-title:Annals of Emergency Medicine

Author:

Martinez Diego A.,Levin Scott R.,Klein Eili Y.,Parikh Chirag R.,Menez Steven,Taylor Richard A.,Hinson Jeremiah S.

Funder

National Institutes of Health

Agency for Healthcare Research and Quality

Centers for Disease Control and Prevention

National Science Foundation

Johns Hopkins University

Emergency Medicine Foundation

Publisher

Elsevier BV

Subject

Emergency Medicine

Reference68 articles.

1. Acute kidney injury and mortality in hospitalized patients;Wang;Am J Nephrol,2012

2. Raising awareness of acute kidney injury: a global perspective of a silent killer;Lewington;Kidney Int,2013

3. Major adverse events one year after acute kidney injury after contrast-enhanced computed tomography;Mitchell;Ann Emerg Med,2015

4. Incidence and consequence of acute kidney injury in unselected emergency admissions to a large acute UK hospital trust;Challiner;BMC Nephrol,2014

5. Clearance and beyond: the complementary roles of GFR measurement and injury biomarkers in acute kidney injury (AKI);Endre;Am J Physiol Ren Physiol,2011

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