Exploring Multilingual Large Language Models for Enhanced TNM Classification of Radiology Report in Lung Cancer Staging
This study underscores the potential of multilingual LLMs for automatic TNM classification in radiology reports. Even without additional model training, performance improvements were evident with the provided TNM definitions, indicating LLMs' relevance in radiology contexts.
Authors
- Takamichi Murakami (ORCID: https://orcid.org/0000-0001-7782-548X)
- Hidetoshi Matsuo (ORCID: https://orcid.org/0000-0002-9684-4632)
- Takaaki Matsunaga
- Koji Fujimoto
- Mizuho Nishio (ORCID: https://orcid.org/0000-0002-6037-2338)
Institutions
- Kyoto University (JP)
- Kobe University (JP)
Publication Details
- Journal
- Cancers
- Published
- 2024-10-26
- DOI
- https://doi.org/10.3390/cancers16213621
- Citations
- 19
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 7.68
Funders
- Japan Society for the Promotion of Science