Using machine learning to discover traumatic brain injury patient phenotypes: national concussion surveillance system Pilot.

Journal: Brain injury
PMID: 38722037

Abstract

OBJECTIVE: The objective is to determine whether unsupervised machine learning identifies traumatic brain injury (TBI) phenotypes with unique clinical profiles.

Authors

  • Dana Waltzman
    Centers for Disease Control and Prevention (CDC), National Center for Injury Prevention and Control (NCIPC), Division of Injury Prevention, Atlanta, Georgia, USA.
  • Jill Daugherty
    Centers for Disease Control and Prevention (CDC), National Center for Injury Prevention and Control (NCIPC), Division of Injury Prevention, Atlanta, Georgia, USA.
  • Alexis Peterson
    Centers for Disease Control and Prevention (CDC), National Center for Injury Prevention and Control (NCIPC), Division of Injury Prevention, Atlanta, Georgia, USA.
  • Angela Lumba-Brown
    Department of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA.

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