Artificial Intelligence Predictions on Long-Term Concussions in Student Athletes
University of Michigan researchers utilize AI to predict long-term health impacts of concussions on college athletes, emphasizing early assessments over injury frequency.
Researchers at the University of Michigan have harnessed the power of artificial intelligence (AI) to forecast the long-term health impacts of sport-related concussions on college student athletes. The study, published in the Annals of Biomedical Engineering, evaluated how AI models can predict changes in key clinical outcomes over an athlete's career, including quality of life, cognitive function, and psychological well-being.
The research involved analyzing data from approximately 3,200 NCAA athletes participating in the Concussion, Assessment, Research, and Education (CARE) Consortium, which gathers health and demographic information from athletes across 30 institutions. Using baseline assessments and follow-up data, the team developed multiple AI models that outperformed simpler prediction methods.
Surprisingly, the study revealed that the initial physical and mental health evaluation at the start of an athlete’s career was the most significant predictor of future outcomes. Conversely, factors like the number or severity of previous concussions, sport type, or exposure to head impacts, appeared to have little influence on long-term symptom progression.
Lead author Lauren Czerniak noted, “This is the first research to leverage AI in predicting how concussions influence clinical outcomes after college sports participation, providing new insights into long-term effects.” The findings challenge assumptions that concussion frequency or intensity directly correlate with future health risks, highlighting the importance of early baseline assessments.
Experts like Steven Broglio emphasize that AI tools can significantly improve concussion diagnosis, management, and long-term care strategies, especially for athletes and military personnel exposed to head impacts. Czerniak envisions future development where AI is integrated into clinical software, allowing personalized risk assessments and proactive health interventions.
Czerniak’s motivation stemmed from her own experiences with concussion recovery, motivating her to contribute to this evolving field. The study’s co-authors include specialists from institutions like Georgia Tech, Wisconsin, Indiana University, and the U.S. Military Academy.
With ongoing research and expanding datasets, AI holds promise for transforming concussion management—aiming to safeguard athletes’ long-term health through innovative predictive tools.
Source: https://medicalxpress.com/news/2025-09-ai-toll-concussions-student-athletes.html
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