aceAssessing the accuracy of ChatGPT-5.6 in American College of Radiology Thyroid Imaging Reporting and Data System feature scoring and classification from synthetic free-text thyroid ultrasound reports
ObjectivesThe American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) provides a standardized framework for thyroid nodule risk stratification based on predefined ultrasound features. This study aimed to evaluate the accuracy and robustness of ChatGPT-5.6 Sol in extracting and scoring ACR TI-RADS features and classifying thyroid nodules from synthetic free-text ultrasound reports.MethodsA primary dataset of 100 synthetic thyroid ultrasound reports was constructed, with each report d…
On synthetic free-text thyroid ultrasound reports, the model identified and scored all five TI-RADS feature categories and assigned the final risk category with no errors against reference annotations.
The reports were synthetic, and the authors state that further validation in larger and more diverse settings is needed to establish generalizability.
Evidence
- Peer-reviewedJournal of International Medical Research2026-10-09
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Truvace Impact Record TRV-2026-1605, v1: “Assessing the accuracy of ChatGPT-5.6 in American College of Radiology Thyroid Imaging Reporting and Data System feature scoring and classification from synthetic free-text thyroid ultrasound reports.” Truvace, 2026-10-16. /record/TRV-2026-1605 (accessed at citation time). sha256 58a71fc4ea8fd18e…
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