Comparison of the accuracy of GPT-4 and resident physicians in differentiating benign and malignant thyroid nodules
Year: 2025
Type: article
Abstract: Objective To assess the diagnostic performance of the GPT-4 model in comparison to resident physicians in distinguishing between benign and malignant thyroid nodules using ultrasound images. Methods This study analyzed 1,145 ultrasound images, including 632 malignant and 513 benign nodules. Both the GPT-4 model and two resident physicians independently classified the nodules using ultrasound images. The diagnostic accuracy of the resident physicians was determined by calculating the average of the individual accuracy rates of the two physicians and this was compared with the performance of the GPT-4 model. Results The GPT-4 model correctly identified 367 out of 632 malignant nodules (58.07%) and 343 out of 513 benign nodules (66.86%). Resident physicians identified 467 malignant (73.89%) and 383 benign nodules (74.66%). There was a statistically significant difference in the classification of malignant nodules ( p < 0.001) and benign nodules ( p = 0.048) between the GPT-4 model and residents. GPT-4 performed better for larger nodules (>1 cm) at 65.38%, compared to 53.77% for smaller nodules (≤1 cm, p = 0.004). The AUC for GPT-4 was 0.67, while residents achieved 0.75. Conclusion The GPT-4 model shows potential in classifying thyroid nodules, but its diagnostic accuracy remains significantly lower than that of resident physicians, particularly for smaller malignant nodules.
Authors: Boxiong Wei, Xiumei Zhang, Yuhong Shao, Xiuming Sun, Luzeng Chen
Institution: Peking University First Hospital
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,353
OpenAlex ID: W4408158895