Enhancing Magnetic Resonance Imaging (MRI) Report Comprehension in Spinal Trauma: Readability Analysis of AI-Generated Explanations for Thoracolumbar Fractures
Overall helpfulness and readability ratings for AI-generated summaries of MRI reports were high, with few inaccuracies recorded. This study demonstrates the potential of GPT-4o to serve as a valuable tool for enhancing patient comprehension of MRI report findings.
Authors
- Paul H. Yi (ORCID: https://orcid.org/0000-0001-9433-8093)
- Calogero Velluto (ORCID: https://orcid.org/0000-0002-3393-5748)
- Kishan S. Shah (ORCID: https://orcid.org/0000-0002-0421-4829)
- Gregory M. Mundis (ORCID: https://orcid.org/0000-0002-1483-7245)
- Michael Pompliano (ORCID: https://orcid.org/0000-0002-3749-8581)
- David C. Sing (ORCID: https://orcid.org/0000-0002-5741-8411)
- Ali Bagheri (ORCID: https://orcid.org/0000-0003-3994-9187)
- Stephen Stephan (ORCID: https://orcid.org/0000-0003-2598-0984)
- Robert K. Eastlack (ORCID: https://orcid.org/0000-0003-2359-1707)
Institutions
- Scripps Health (US)
- St. Jude Children's Research Hospital (US)
- Torrey Pines Institute For Molecular Studies (US)
- Scripps Clinic (US)
Publication Details
- Journal
- JMIR AI
- Published
- 2025-05-14
- DOI
- https://doi.org/10.2196/69654
- Citations
- 1
- Primary Topic
- Medical Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.67