Internal and External Validation of a Machine Learning Risk Score for Acute Kidney Injury-Reference-Cited by-同舟云学术

Internal and External Validation of a Machine Learning Risk Score for Acute Kidney Injury

Published:2020-08-11 Issue:8 Volume:3 Page:e2012892
ISSN:2574-3805
Container-title:JAMA Network Open
language:en
Short-container-title:JAMA Netw Open

Author:

Churpek Matthew M.¹,Carey Kyle A.²,Edelson Dana P.²,Singh Tripti¹,Astor Brad C.¹³,Gilbert Emily R.⁴,Winslow Christopher⁵,Shah Nirav²⁵,Afshar Majid⁴,Koyner Jay L.²

Affiliation:

1. Department of Medicine, University of Wisconsin, Madison

2. Department of Medicine, The University of Chicago, Illinois

3. Department of Population Health Sciences, University of Wisconsin, Madison

4. Department of Medicine, Loyola University Medical Center, Maywood, Illinois

5. Department of Medicine, NorthShore University Healthcare, Evanston, Illinois

Publisher

American Medical Association (AMA)

Subject

General Medicine

Link

https://jamanetwork.com/journals/jamanetworkopen/articlepdf/2769146/churpek_2020_oi_200490.pdf

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4. Tissue inhibitor metalloproteinase-2 (TIMP-2) • IGF-binding protein-7 (IGFBP7) levels are associated with adverse outcomes in patients in the intensive care unit with acute kidney injury.;Xie;Kidney Int,2019

5. The association of angiogenesis markers with acute kidney injury and mortality after cardiac surgery.;Mansour;Am J Kidney Dis,2019

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