Comparative Analysis of Large Language Models for Answering Cancer-Related Questions in Korean.

Journal: Yonsei medical journal
Published Date: Jul 1, 2025

Abstract

PURPOSE: Large language models (LLMs) have shown potential in medicine, transforming patient education, clinical decision support, and medical research. However, the effectiveness of LLMs in providing accurate medical information, particularly in non-English languages, remains underexplored. This study aimed to compare the quality of responses generated by ChatGPT and Naver's CLOVA X to cancer-related questions posed in Korean.

Authors

  • Hyun Chang
    Department of Medical Oncology and Hematology, International St. Mary's Hospital, Catholic Kwandong University, Incheon, Korea. hchang@ish.ac.kr.
  • Jin-Woo Jung
    Department of Computer Science and Engineering, Dongguk University, Seoul 04620, Korea.
  • Yongho Kim
    Department of Radiation Oncology, International St. Mary's Hospital, Catholic Kwandong University, Incheon, Korea.

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