The utility of machine learning for predicting donor discard in abdominal transplantation.

Journal: Clinical transplantation
Published Date: Mar 8, 2023

Abstract

BACKGROUND: Increasing access and better allocation of organs in the field of transplantation is a critical problem in clinical care. Limitations exist in accurately predicting allograft discard. Potential exists for machine learning to provide a balanced assessment of the potential for an organ to be used in a transplantation procedure.

Authors

  • Rowland W Pettit
    Department of Medicine, Baylor College of Medicine, Houston, Texas, USA.
  • Britton B Marlatt
    Research and Development, InformAI, Houston, Texas.
  • Travis J Miles
    Department of Surgery, Division of Abdominal, Transplantation, Baylor College of Medicine, Houston, Texas, USA.
  • Selim Uzgoren
    Research and Development, InformAI, Houston, Texas.
  • Stuart J Corr
    DeBakey Heart and Vascular Center, Houston Methodist Hospital, Houston, Texas.
  • Anil Shetty
    Ferronova Pty Ltd, Adelaide, South Australia, Australia.
  • Jim Havelka
    InformAI, Houston, Texas.
  • Abbas Rana
    Department of Medicine, Baylor College of Medicine, Houston, Texas, USA.

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