Source Characteristics Influence AI-Enabled Orthopaedic Text Simplification
This study provides critical insights into the ability of LLMs to simplify complex orthopaedic PEMs, enhancing their readability without compromising informational integrity. By identifying predictive factors for successful text transformation, this research supports the application of AI in improving health literacy, potentially leading to better patient comprehension and outcomes in orthopaedic care.
Authors
- Bryce Picton (ORCID: https://orcid.org/0000-0003-3539-6167)
- Sean S. Solomon (ORCID: https://orcid.org/0000-0002-4001-6141)
- John A. Scolaro (ORCID: https://orcid.org/0000-0001-7926-5017)
- Ariana M. Nelson (ORCID: https://orcid.org/0000-0003-1575-1635)
- Saman Andalib (ORCID: https://orcid.org/0009-0002-3281-8256)
- Aidin Spina (ORCID: https://orcid.org/0000-0003-3994-9646)
Institutions
- University of California, Irvine (US)
- University of California, Irvine Medical Center (US)
Publication Details
- Journal
- JBJS Open Access
- Published
- 2025-01-01
- DOI
- https://doi.org/10.2106/jbjs.oa.24.00007
- Citations
- 6
- Primary Topic
- Text Readability and Simplification
- Type
- article
- Field-Weighted Citation Impact
- 14.89
Funders
- University of California, Irvine