Your browser doesn't support javascript.
loading
Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study.
Huang, Chenxi; Murugiah, Karthik; Mahajan, Shiwani; Li, Shu-Xia; Dhruva, Sanket S; Haimovich, Julian S; Wang, Yongfei; Schulz, Wade L; Testani, Jeffrey M; Wilson, Francis P; Mena, Carlos I; Masoudi, Frederick A; Rumsfeld, John S; Spertus, John A; Mortazavi, Bobak J; Krumholz, Harlan M.
Afiliação
  • Huang C; Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, Connecticut, United States of America.
  • Murugiah K; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America.
  • Mahajan S; Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, Connecticut, United States of America.
  • Li SX; Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, Connecticut, United States of America.
  • Dhruva SS; Robert Wood Johnson Foundation Clinical Scholars Program, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America.
  • Haimovich JS; Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, United States of America.
  • Wang Y; Albert Einstein College of Medicine, Bronx, New York, United States of America.
  • Schulz WL; Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, Connecticut, United States of America.
  • Testani JM; Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, Connecticut, United States of America.
  • Wilson FP; Department of Laboratory Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America.
  • Mena CI; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America.
  • Masoudi FA; Section of Nephrology, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America.
  • Rumsfeld JS; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America.
  • Spertus JA; Division of Cardiology, School of Medicine, University of Colorado, Aurora, Colorado, United States of America.
  • Mortazavi BJ; Division of Cardiology, School of Medicine, University of Colorado, Aurora, Colorado, United States of America.
  • Krumholz HM; Department of Cardiology, Saint Luke's Mid America Heart Institute, Kansas City, Missouri, United States of America.
PLoS Med ; 15(11): e1002703, 2018 11.
Article em En | MEDLINE | ID: mdl-30481186
Assuntos
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Técnicas de Apoio para a Decisão / Mineração de Dados / Injúria Renal Aguda / Intervenção Coronária Percutânea / Aprendizado de Máquina Tipo de estudo: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2018 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Técnicas de Apoio para a Decisão / Mineração de Dados / Injúria Renal Aguda / Intervenção Coronária Percutânea / Aprendizado de Máquina Tipo de estudo: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2018 Tipo de documento: Article