A Machine Learning Approach to Concussion Risk Estimation Among Players Exhibiting Visible Signs in Professional Hockey.

Journal: Sports medicine (Auckland, N.Z.)
PMID: 39287776

Abstract

BACKGROUND: The identification of concussion risk factors, such as visible signs and mechanisms of injury, improves concussion identification. Exploring individual risk factors, such as concussion history, may help to improve existing concussion risk models and algorithms.

Authors

  • Jared M Bruce
    Department of Biomedical and Health Informatics, University of Missouri-Kansas City School of Medicine, Kansas City, MO, 64108, USA. brucejm@umkc.edu.
  • Kaitlin E Riegler
    Princeton Neuropsychology and Sports Concussion Center of New Jersey at RSM Psychology, Princeton, NJ, 08540, USA.
  • Willem Meeuwisse
    Department of Kinesiology, University of Calgary, Calgary, Alberta, Canada. w.meeuwisse@ucalgary.ca.
  • Paul Comper
    Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, ON, MS55 1A1, Canada.
  • Michael G Hutchison
    Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, ON, MS55 1A1, Canada.
  • J Scott Delaney
    McGill Sport Medicine Clinic, Montreal, QC, Canada.
  • Ruben J Echemendia
    Psychological and Neurobehavioral Associates, Inc., State College, PA, 16801, USA.

Keywords

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