A machine learning approach for the prediction of overall deceased donor organ yield.

Journal: Surgery
Published Date: Nov 1, 2021

Abstract

BACKGROUND: Optimizing organ yield (number of organs transplanted per donor) is a potentially modifiable way to increase the number of organs available for transplant. Models to predict the expected deceased donor organ yield have been developed based on ordinary least squares regression and logistic regression. However, alternative modeling methodologies incorporating machine learning may have superior performance compared with conventional approaches.

Authors

  • Wesley J Marrero
    MGH Institute for Technology Assessment, Harvard Medical School, Boston, MA.
  • Mariel S Lavieri
    Department of Industrial and Operations Engineering, University of Michigan College of Engineering, Ann Arbor, Michigan.
  • Seth D Guikema
    Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI.
  • David W Hutton
    School of Public Health, University of Michigan Ann Arbor, MI.
  • Neehar D Parikh
    Department of Internal Medicine, University of Michigan, Ann Arbor, MI. Electronic address: ndparikh@med.umich.edu.

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