Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study-Reference-Cited by-同舟云学术

Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study

Published:2018-11-27 Issue:11 Volume:15 Page:e1002703
ISSN:1549-1676
Container-title:PLOS Medicine
language:en
Short-container-title:PLoS Med

Author:

Huang Chenxi,Murugiah Karthik,Mahajan Shiwani,Li Shu-Xia,Dhruva Sanket S.,Haimovich Julian S.,Wang Yongfei,Schulz Wade L.^ORCID,Testani Jeffrey M.,Wilson Francis P.^ORCID,Mena Carlos I.,Masoudi Frederick A.^ORCID,Rumsfeld John S.,Spertus John A.,Mortazavi Bobak J.^ORCID,Krumholz Harlan M.^ORCID

Publisher

Public Library of Science (PLoS)

Subject

General Medicine

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4. Sodium bicarbonate-based hydration prevents contrast-induced nephropathy: a meta-analysis;P Meier;BMC Med,2009

5. Does safe dosing of iodinated contrast prevent contrast-induced acute kidney injury?;JR Brown;Circ Cardiovasc Interv,2010

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