Development of a Large-Scale Dataset of Chest Computed Tomography Reports in Japanese and a High-Performance Finding Classification Model: Dataset Development and Validation Study.

Journal: JMIR medical informatics
Published Date:

Abstract

BACKGROUND: Recent advances in large language models have highlighted the need for high-quality multilingual medical datasets. Although Japan is a global leader in computed tomography (CT) scanner deployment and use, the absence of large-scale Japanese radiology datasets has hindered the development of specialized language models for medical imaging analysis. Despite the emergence of multilingual models and language-specific adaptations, the development of Japanese-specific medical language models has been constrained by a lack of comprehensive datasets, particularly in radiology.

Authors

  • Yosuke Yamagishi
    Department of Radiology, Saitama Medical University, 38 Morohongou, Moroyama-machi, Iruma-gun, Saitama, Japan.
  • Yuta Nakamura
    Division of Radiology and Biomedical Engineering, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan. yutanakamura-tky@umin.ac.jp.
  • Tomohiro Kikuchi
    Department of Radiology, Jichi Medical University, Tochigi, Japan.
  • Yuki Sonoda
    Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
  • Hiroshi Hirakawa
    Akira Katayama, MD; Koichiro Yasaka, MD, PhD; Hiroshi Hirakawa, MD; Yuta Ohtake, MD; and Osamu Abe, MD, PhD, work for the University of Tokyo.
  • Shintaro Kano
    Department of Diagnostic Radiology, Toranomon Hospital, Tokyo, Japan.
  • Satoshi Nakamura
    Radiation Safety and Quality Assurance Division, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, Japan.
  • Shouhei Hanaoka
    Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan.
  • Takeharu Yoshikawa
    The University of Tokyo Hospital.
  • Osamu Abe
    From the Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan 113-8655.