Comparative Analysis of Large Language Models in the Interpretation of Gynecologic Pathology Reports
Abstract
This letter evaluates the performance of three large language models in explaining gynecologic pathology reports to patients. Using synthetic cases ranging from benign to malignant diagnoses, the author compares readability, emotional tone, and medical jargon density, highlighting clinically relevant differences in patient-centered communication styles.
Fields of Study & Subjects
Topic Modeling
Machine Learning in Healthcare
Artificial Intelligence in Healthcare and Education
Publication details
- Journal / source
- European Journal of Innovative Medical Research
- Volume
- 1
- Issue
- 1
- Pages
- 31–33
- Publication date
- 5 January 2026