AUTHOR=Henriquez Maria , Sumner Jacob , Faherty Mallory , Sell Timothy , Bent Brinnae 

TITLE=Machine Learning to Predict Lower Extremity Musculoskeletal Injury Risk in Student Athletes

JOURNAL=Frontiers in Sports and Active Living

VOLUME=Volume 2 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/sports-and-active-living/articles/10.3389/fspor.2020.576655

DOI=10.3389/fspor.2020.576655

ISSN=2624-9367

ABSTRACT=Injury rates in student athletes are high and often unpredictable. Injury risk factors are not agreed upon and often not validated. Here, we present a machine learning methodology for identifying the most significant injury risk factors and develop a model of lower extremity musculoskeletal injury risk in student athletes with physical performance metrics spanning strength, postural stability, and flexibility combined with previous injury metrics. We tested our model in a population of 122 student athletes with performance metrics for the lower musculoskeletal system and achieved an injury risk accuracy of 79%. By incorporating machine learning into determining injury risk, we can increase accuracy of injury risk assessments, implement timely interventions, and decrease the number of career-ending or chronic injuries among student athletes.