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Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study.
PLoS Med
68
2018
AKI, acute kidney injury, patients, women
Acute Kidney Injury, Aged, Clinical Decision-Making, Data Mining, Decision Support Techniques, Female, Humans, Machine Learning, Male, Middle Aged, Percutaneous Coronary Intervention, Protective Factors, Registries, Reproducibility of Results, Retrospective Studies, Risk Assessment, Risk Factors, Time Factors, Treatment Outcome
Author NameAffiliation
Chenxi HuangCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital
Karthik MurugiahYale School of Medicine
Shiwani MahajanCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital
Shu-Xia LiCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital
Sanket S DhruvaRobert Wood Johnson Foundation Clinical Scholars Program, Yale School of Medicine
Sanket S DhruvaVeterans Affairs Connecticut Healthcare System
Julian S HaimovichAlbert Einstein College of Medicine
Yongfei WangCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital
Wade Schulz (CM4AI)Center for Outcomes Research and Evaluation, Yale-New Haven Hospital
Wade Schulz (CM4AI)Yale School of Medicine
Jeffrey M TestaniYale School of Medicine
Francis P WilsonYale School of Medicine
Carlos Mena-HurtadoYale School of Medicine
Frederick A MasoudiUniversity of Colorado
John S RumsfeldUniversity of Colorado
John A SpertusSaint Luke's Mid America Heart Institute
John A SpertusSaint Luke's Mid America Heart Institute
Bobak J MortazaviTexas A&M University, College Station
Bobak J MortazaviTexas A&M University, College Station
Harlan M KrumholzCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital
Harlan M KrumholzYale School of Medicine
Harlan M KrumholzYale School of Public Health
Harlan M KrumholzCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital
Harlan M KrumholzYale School of Medicine
Harlan M KrumholzYale School of Public Health
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