Efficient Maintenance of Large-Scale Medical Dictionaries Using Large Language Models: A Case for Biomarkers.

Journal: Studies in health technology and informatics
Published Date: Aug 7, 2025

Abstract

Dictionaries are essential in natural language processing and provide significant value across tasks; however, their construction and maintenance are expensive. Leveraging manual revision histories to suggest automatic corrections for unedited terms offers a promising solution to enhance quality while reducing costs. This study proposes a method for automatically correcting metadata in a large-scale medical dictionary containing more than 500,000 terms. By utilizing large language models that excel in zero-shot settings, the system estimates the dictionary information without task-specific configurations. This method was demonstrated through experiments on variations in gene biomarker expression, a task that requires specialized medical knowledge. The results indicate that this approach can significantly reduce the dictionary maintenance burden.

Authors

  • Yuka Otsuki
    Department of Information Science, Nara Institute of Science and Technology, Ikoma, Japan.
  • Shuntaro Yada
    Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Nara, Japan.
  • Tomohiro Nishiyama
    Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology, Nara, Japan.
  • Toshiyuki Sakurai
    Prime Research Institute for Medical RWD, Inc., Japan.
  • Masafumi Okada
    Prime Research Institute for Medical RWD, Inc., Japan.
  • Noriko Kudo
    Department of Information Science, Nara Institute of Science and Technology, Ikoma, Japan.
  • Kyoko Kawabata
    Nara Institute of Science and Technology, Japan.
  • Takako Fujimaki
    Department of Information Science, Nara Institute of Science and Technology, 8916-5 Takayamacho, Ikoma, 630-0101, Nara, Japan.
  • Hiroyuki Nagai
    Nara Institute of Science and Technology, 8916-5, Takayama-cho, Ikoma-shi, Nara, 630-0192, Japan, 81 743-72-5250.
  • Shoko Wakamiya
    Nara Institute of Science and Technology (NAIST), Japan.
  • Eiji Aramaki
    Nara Institute of Science and Technology (NAIST), Japan.

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