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
Our study established a robust Japanese CT report dataset and demonstrated the effectiveness of a specialized language model in structured classification of findings. This hybrid approach of machine translation and expert validation enabled the creation of large-scale datasets while maintaining high-quality standards. This study provides essential resources for advancing medical artificial intelligence research in Japanese health care settings, using datasets and models publicly available for research to facilitate further advancement in the field.
Authors
- Yosuke Yamagishi (ORCID: https://orcid.org/0009-0006-7688-3075)
- Tomohiro Kikuchi (ORCID: https://orcid.org/0000-0002-4222-4569)
- Osamu Abe (ORCID: https://orcid.org/0000-0002-1180-2629)
- T. Yoshikawa (ORCID: https://orcid.org/0000-0002-1924-5468)
- Shouhei Hanaoka (ORCID: https://orcid.org/0000-0002-7496-1651)
- Yuta Nakamura (ORCID: https://orcid.org/0000-0001-6962-6704)
- Shintaro Kano (ORCID: https://orcid.org/0000-0003-1432-3815)
- Yuki Sonoda (ORCID: https://orcid.org/0009-0005-8622-2433)
- Satoshi N. Nakamura
- Hisashi Hirakawa (ORCID: https://orcid.org/0009-0004-2444-4228)
Institutions
- Jichi Medical University (JP)
- University of Tokyo Hospital (JP)
- Toranomon Hospital (JP)
- The University of Tokyo (JP)
Publication Details
- Journal
- JMIR Medical Informatics
- Published
- 2025-08-28
- DOI
- https://doi.org/10.2196/71137
- Citations
- 1
- Primary Topic
- Topic Modeling
- Type
- article
- Field-Weighted Citation Impact
- 2.48
Funders
- Japan Society for the Promotion of Science