Skip to main content
Browse by:

Data Dialogue: Tim Sell (K-Lab)

Rhodes Information Initiative
Friday, October 04, 2019
11:45 am - 12:45 pm
Tim Sell (K-Lab)

Musculoskeletal Injury Prevention through Machine Learning
Musculoskeletal injuries are a substantial problem for active populations including student-athletes and military personnel. In the military, they are the primary source of disability cases; account for the majority of discharges from the service; and significantly impact military readiness. In athletic populations, they result in a significant number of days lost and can also result short-term and long- term health issues including post-traumatic osteoarthritis. One of the most notable consequences of musculoskeletal injury is reinjury following return-to-duty or return-to-play. There is evidence demonstrating that some individuals demonstrate residual musculoskeletal and neuromuscular deficits upon return to activity, but these deficits are not consistent in magnitude or type indicating the need to identify the individual-specific risk factors that predispose and individual to reinjury. Predicting musculoskeletal reinjury risk through mathematical modeling has the potential to transform musculoskeletal injury prevention by identifying individualized reinjury risk that can guide return-to-duty and return-to-play decisions.

Contact: Ariel Dawn