Machine Learning for the Prediction of Survival Post-Allogeneic Hematopoietic Cell Transplantation: A Single-Center Experience.

Journal: Acta haematologica
Published Date: Sep 28, 2023

Abstract

INTRODUCTION: Prediction of outcomes following allogeneic hematopoietic cell transplantation (HCT) remains a major challenge. Machine learning (ML) is a computational procedure that may facilitate the generation of HCT prediction models. We sought to investigate the prognostic potential of multiple ML algorithms when applied to a large single-center allogeneic HCT database.

Authors

  • Hamed Shourabizadeh
    Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario, Canada.
  • Dionne M Aleman
    Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario M5S 3G8, Canada.
  • Louis-Martin Rousseau
    Polytechnique Montréal, Montreal, Canada.
  • Arjun D Law
    Hans Messner Allogeneic Transplant Program, Princess Margaret Cancer Centre, University of Toronto, Toronto, Ontario, Canada.
  • Auro Viswabandya
    Hans Messner Allogeneic Transplant Program, Princess Margaret Cancer Centre, University of Toronto, Toronto, Ontario, Canada.
  • Fotios V Michelis
    Hans Messner Allogeneic Transplant Program, Princess Margaret Cancer Centre, University of Toronto, Toronto, Ontario, Canada.

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