Prediction of Pathological Complete Response after Chemoradiation for Locally Advanced Rectal Cancer Using Machine Learning with Clinical Features, the INTERCEPTOR Study Preliminary Model
- DOI
- 10.23922/jarc.2025-106
- Published
- 2026-07-25
- Container
- Journal of the Anus, Rectum and Colon
- Publisher
- The Japan Society of Coloproctology
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.23922/jarc.2025-106,
title = {Prediction of Pathological Complete Response after Chemoradiation for Locally Advanced Rectal Cancer Using Machine Learning with Clinical Features, the INTERCEPTOR Study Preliminary Model},
author = {David Mens and Soogyeong Shin and Farhan Akram and Andrew Stubbs and Michail Doukas and Cornelis Verhoef and Denise Hilling and Jan von der Thüsen},
year = {2026},
journal = {Journal of the Anus, Rectum and Colon},
doi = {10.23922/jarc.2025-106},
url = {https://doi.org/10.23922/jarc.2025-106}
}RIS
TY - JOUR TI - Prediction of Pathological Complete Response after Chemoradiation for Locally Advanced Rectal Cancer Using Machine Learning with Clinical Features, the INTERCEPTOR Study Preliminary Model AU - David Mens AU - Soogyeong Shin AU - Farhan Akram AU - Andrew Stubbs AU - Michail Doukas AU - Cornelis Verhoef AU - Denise Hilling AU - Jan von der Thüsen PY - 2026 JO - Journal of the Anus, Rectum and Colon DO - 10.23922/jarc.2025-106 UR - https://doi.org/10.23922/jarc.2025-106 ER -
APA
Mens, D., Shin, S., Akram, F., Stubbs, A., Doukas, M., Verhoef, C., Hilling, D., & Thüsen, J. V. D. (2026). Prediction of Pathological Complete Response after Chemoradiation for Locally Advanced Rectal Cancer Using Machine Learning with Clinical Features, the INTERCEPTOR Study Preliminary Model. Journal of the Anus, Rectum and Colon. https://doi.org/10.23922/jarc.2025-106
Source records
- crossref · retrieved 2026-09-26T22:06:10.640Z