A Machine Learning Method for Allocating Scarce COVID-19 Monoclonal Antibodies.

Journal: JAMA health forum
PMID: 39269694

Abstract

IMPORTANCE: During the COVID-19 pandemic, the effective distribution of limited treatments became a crucial policy goal. Yet, limited research exists using electronic health record data and machine learning techniques, such as policy learning trees (PLTs), to optimize the distribution of scarce therapeutics.

Authors

  • Mengli Xiao
    Division of Biostatistics, University of Minnesota, Minneapolis, Minnesota.
  • Kyle C Molina
    Department of Emergency Medicine, University of Colorado School of Medicine, Aurora.
  • Neil R Aggarwal
    Division of Pulmonary Sciences, Department of Medicine, University of Colorado School of Medicine, Aurora.
  • Laurel E Beaty
    Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora.
  • Tellen D Bennett
    Section of Informatics and Data Science, Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO.
  • Nichole E Carlson
    Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora.
  • Lindsey E Fish
    Division of General Internal Medicine, Denver Health, Denver, Colorado.
  • Mika K Hamer
    Center for Bioethics and Humanities, University of Colorado Anschutz Medical Campus, Aurora.
  • Bethany M Kwan
    Department of Emergency Medicine, University of Colorado School of Medicine, Aurora.
  • David A Mayer
    Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora.
  • Jennifer L Peers
    Department of Emergency Medicine, University of Colorado School of Medicine, Aurora.
  • Matthew K Wynia
    Center for Bioethics and Humanities, University of Colorado Anschutz Medical Campus, Aurora.
  • Adit A Ginde
    Department of Emergency Medicine, University of Colorado School of Medicine, Aurora.

Keywords

External Resources

Popular Topics
Recent Journals