Accuracy of large language models in thyroid nodule-related questions based on the Korean thyroid imaging reporting and data system (K-TIRADS)

Abstract

We read with great pleasure the review article “Updated Primer on Generative Artificial Intelligence and Large Language Models in Medical Imaging for Medical Professionals” by Kim et al. [1] which was published online in the Korean Journal of Radiology in February. The authors impressively presented a very comprehensive overview of generative artificial intelligence, and also discussed the background and working principles of large language models (LLMs). Inspired by this article, we would like to present this letter, in which we investigate the performance of LLMs on questions related to thyroid nodules based on the Korean Thyroid Imaging Reporting and Data System (K-TIRADS).