A Racially Unbiased, Machine Learning Approach to Prediction of Mortality: Algorithm Development Study.

Journal: JMIR public health and surveillance
PMID: 33090117

Abstract

BACKGROUND: Racial disparities in health care are well documented in the United States. As machine learning methods become more common in health care settings, it is important to ensure that these methods do not contribute to racial disparities through biased predictions or differential accuracy across racial groups.

Authors

  • Angier Allen
  • Samson Mataraso
    Dascena, Inc., San Francisco, CA, USA.
  • Anna Siefkas
    Dascena, Inc., San Francisco, CA, USA. Electronic address: anna@dascena.com.
  • Hoyt Burdick
    Cabell Huntington Hospital, Huntington, WV, USA; Marshall University School of Medicine, Huntington, WV, USA.
  • Gregory Braden
    Kidney Care and Transplant Associates of New England, Springfield, MA, USA.
  • R Phillip Dellinger
    Division of Critical Care Medicine, Cooper University Hospital/Cooper Medical School of Rowan University, Camden, NJ, USA.
  • Andrea McCoy
    Cape Regional Medical Center, Cape May Court House, New Jersey, USA.
  • Emily Pellegrini
  • Jana Hoffman
    Dascena Inc., San Francisco, CA, United States.
  • Abigail Green-Saxena
    Dascena, Inc., USA.
  • Gina Barnes
    Dascena, Inc., San Francisco, CA, USA.
  • Jacob Calvert
    Dascena Inc., Hayward, California, USA.
  • Ritankar Das
    Dascena, Inc, Hayward, California, USA.

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