Sport-Specific Craniofacial Injury Risk Stratification in Squash, Badminton, and Tennis Using NEISS and ChatGPT
While ChatGPT4-o can provide accessible, structured information, its performance in this study demonstrated moderate reliability, low treatment guidance quality, a reading level above AMA recommendations, and moderately high specificity. These findings underscore the need for cautious integration of AI tools in patient education and clinical decision-making. As LLMs evolve, there is potential for risk stratification and injury prevention tools to improve. Careful development and validation will be integral to ensure safe and effective clinical use, as well as HIPAA compliance, lack of bias, and accurate information.
Authors
- Kate M Miller (ORCID: https://orcid.org/0000-0002-1142-7697)
- Kristen Dean
- Wrood Kassira (ORCID: https://orcid.org/0000-0001-7803-3038)
- Seth Ray Thaller (ORCID: https://orcid.org/0000-0003-0190-0812)
- Baylee M. Brochu
- Savanah R. Sturm
Institutions
- University of Miami (US)
Publication Details
- Journal
- Journal of Craniofacial Surgery
- Published
- 2026-02-25
- DOI
- https://doi.org/10.1097/scs.0000000000012095
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00