Machine Learning Compared With Conventional Statistical Models for Predicting Myocardial Infarction Readmission and Mortality: A Systematic Review.

Journal: The Canadian journal of cardiology
Published Date: Mar 5, 2021

Abstract

BACKGROUND: Machine learning (ML) methods are increasingly used in addition to conventional statistical modelling (CSM) for predicting readmission and mortality in patients with myocardial infarction (MI). However, the two approaches have not been systematically compared across studies of prognosis in patients with MI.

Authors

  • Sung Min Cho
    Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada; University of Toronto, Toronto, Ontario, Canada.
  • Peter C Austin
    Institute for Clinical Evaluative Service (ICES), Toronto, Ontario, Canada; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada.
  • Heather J Ross
    Ted Rogers Centre for Heart Research, University of Toronto, Ontario, Canada (Y.M., F.F., Y.G., B.K., E.D.L., M.B., D.H.B., J.D., A.S., C.M.I., H.J.R.).
  • Husam Abdel-Qadir
    Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada; Peter Munk Cardiac Centre, University Health Network, Toronto, Ontario, Canada; Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada; Institute for Health Policy, Management and Evaluation, Toronto, Ontario, Canada; Women's College Hospital, Toronto, Ontario, Canada; University of Toronto, Toronto, Ontario, Canada.
  • Davide Chicco
    Dipartimento di Informatica Sistemistica e Comunicazione, Università di Milano-Bicocca, Milan, Italy.
  • George Tomlinson
    Institute for Health Policy, Management and Evaluation, Toronto, Ontario, Canada; Biostatistics Research Unit, University Health Network, Toronto, Ontario, Canada; University of Toronto, Toronto, Ontario, Canada.
  • Cameron Taheri
    Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada; University of Toronto, Toronto, Ontario, Canada.
  • Farid Foroutan
    Ted Rogers Centre for Heart Research, University of Toronto, Ontario, Canada (Y.M., F.F., Y.G., B.K., E.D.L., M.B., D.H.B., J.D., A.S., C.M.I., H.J.R.).
  • Patrick R Lawler
    Divisions of Cardiology and Clinical Epidemiology, Jewish General Hospital/McGill University, Montreal, Quebec, Canada.
  • Filio Billia
    Peter Munk Cardiac Centre, University Health Network, Toronto, Ontario, Canada; Toronto General Hospital Research Institute, Toronto, Ontario, Canada; University of Toronto, Toronto, Ontario, Canada.
  • Anthony Gramolini
    Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada; University of Toronto, Toronto, Ontario, Canada.
  • Slava Epelman
    Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada; Peter Munk Cardiac Centre, University Health Network, Toronto, Ontario, Canada; Toronto General Hospital Research Institute, Toronto, Ontario, Canada; University of Toronto, Toronto, Ontario, Canada.
  • Bo Wang
    Department of Clinical Laboratory Medicine Center, Inner Mongolia Autonomous Region People's Hospital, Hohhot, Inner Mongolia, China.
  • Douglas S Lee
    Ted Rogers Centre for Heart Research, Toronto, Ontario, Canada; Peter Munk Cardiac Centre, University Health Network, Toronto, Ontario, Canada; Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada; Institute for Health Policy, Management and Evaluation, Toronto, Ontario, Canada; Toronto General Hospital Research Institute, Toronto, Ontario, Canada; University of Toronto, Toronto, Ontario, Canada. Electronic address: dlee@ices.on.ca.

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