Elucidating Celecoxib's Preventive Effect in Capecitabine-Induced Hand-Foot Syndrome Using Medical Natural Language Processing
These findings demonstrate the effectiveness of NLP in detecting HFS from real-world clinical records. The application to celecoxib-HFS detection illustrates the potential utility of this approach for retrospective safety analysis. Further work is needed to evaluate generalizability across diverse clinical settings.
Authors
- Tomohisa Seki (ORCID: https://orcid.org/0000-0002-4281-135X)
- Shungo Imai (ORCID: https://orcid.org/0000-0001-5706-613X)
- Shuntaro Yada (ORCID: https://orcid.org/0000-0002-6209-1054)
- Kiminori Shimamoto (ORCID: https://orcid.org/0000-0003-0838-7505)
- Yoshimasa Kawazoe (ORCID: https://orcid.org/0000-0002-7277-0827)
- Emiko Shinohara
- Masami Tsuchiya (ORCID: https://orcid.org/0000-0003-3846-0435)
- Eiji Aramaki (ORCID: https://orcid.org/0000-0003-0201-3609)
- Hayato Kizaki (ORCID: https://orcid.org/0000-0002-4572-1333)
- Shoko Wakamiya (ORCID: https://orcid.org/0000-0002-9371-1340)
- Satoko Hori (ORCID: https://orcid.org/0000-0002-4596-5418)
Institutions
- University of Tsukuba (JP)
- Keio University (JP)
- University of Tokyo Hospital (JP)
- Artificial Intelligence in Medicine (Canada) (CA)
- Nara Institute of Science and Technology (JP)
Publication Details
- Journal
- JCO Clinical Cancer Informatics
- Published
- 2025-08-01
- DOI
- https://doi.org/10.1200/cci-25-00096
- Citations
- 1
- Primary Topic
- Chemotherapy-related skin toxicity
- Type
- article
- Field-Weighted Citation Impact
- 2.00