Risk prediction model for in-hospital mortality in women with ST-elevation myocardial infarction: A machine learning approach.

Journal: Heart & lung : the journal of critical care
Published Date: Jan 1, 2017

Abstract

BACKGROUND: Studies had shown that mortality due to ST-elevation myocardial infarction (STEMI) is higher in women compared with men. The purpose of this study is to develop and validate prediction models for all-cause in-hospital mortality in women admitted with STEMI using logistic regression and random forest, and to compare the performance and validity of the different models.

Authors

  • Hend Mansoor
    Department of Health Services Research, University of Florida, College of Public Health, Gainesville, FL, USA. Electronic address: hmansoor@ufl.edu.
  • Islam Y Elgendy
    Department of Cardiovascular Diseases, University of Florida, Gainesville, Florida.
  • Richard Segal
    Department of Pharmaceutical Outcomes and Policy, College of Pharmacy, Gainesville, FL, USA.
  • Anthony A Bavry
    Division of Cardiovascular Medicine, Department of Medicine, Gainesville, FL, USA.
  • Jiang Bian
    Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida, United States of America.

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