Prediction of the Therapeutic Response to Neoadjuvant Chemotherapy for Rectal Cancer Using a Deep Learning Model
The non-invasive deep learning model using prechemotherapy CT images exhibited high predictive performance in predicting the pathological therapeutic response to SOX NAC.
Authors
- Kenichi Hakamada (ORCID: https://orcid.org/0000-0001-6513-1202)
- Masashi Matsuzaka (ORCID: https://orcid.org/0000-0002-8199-3037)
- Taiichi Wakiya (ORCID: https://orcid.org/0000-0003-3681-7736)
- Yoshihiro Sasaki
- Hajime Morohashi
- Yoshiyuki Sakamoto
- Taishu Kanda (ORCID: https://orcid.org/0000-0003-2839-3347)
- Takuya Miura (ORCID: https://orcid.org/0000-0002-0238-2845)
- Shunsuke Kubota
Institutions
- Hirosaki University (JP)
- Hirosaki University Hospital (JP)
Publication Details
- Journal
- Journal of the Anus Rectum and Colon
- Published
- 2025-04-24
- DOI
- https://doi.org/10.23922/jarc.2024-085
- Primary Topic
- Colorectal Cancer Surgical Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Hirosaki University