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Vision Training Methods for Sports Concussion Mitigation and Management
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Machine Learning in Modeling High School Sport Concussion Symptom Resolve.

Michael F Bergeron1, Sara Landset2, Todd A Maugans3

  • 1SIVOTEC Analytics, Boca Raton, FL.

Medicine and Science in Sports and Exercise
|January 30, 2019
PubMed
Summary
This summary is machine-generated.

Machine learning models can predict concussion recovery time in high school athletes. This approach aids in managing sports-related concussions and supports clinical decision-making for athletes.

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Area of Science:

  • Sports Medicine
  • Data Science
  • Neurology

Background:

  • Concussion prevalence in sports is high, posing challenges for clinical management and return-to-play decisions.
  • Predicting the resolution time of concussion symptoms is crucial for effective treatment planning.

Purpose of the Study:

  • To implement a supervised machine learning approach for estimating symptom resolution time in high school athletes after a concussion.
  • To evaluate the efficacy of various machine learning algorithms in predicting concussion recovery.

Main Methods:

  • Examined 10 classification algorithms using machine learning to predict symptom resolution within 7, 14, or 28 days.
  • Utilized a dataset of 3 years of concussions from high school football and other contact sports.

Main Results:

  • Headache, dizziness, and difficulty concentrating were the most common concussion symptoms.
  • Naïve Bayes and Random Forest models showed the best performance in predicting symptom resolution time, with an area under the curve between 0.656 and 0.742.
  • Statistically significant performance differences were observed across the 10 classification models.

Conclusions:

  • Supervised machine learning demonstrates efficacy in developing symptom-based prediction models for sport-related concussion recovery.
  • These models can enhance clinical decision support for managing concussions in athletes.
  • Further exploration is warranted to refine these predictive models.