Development and Cross-Institutional Validation of a Comprehensive Machine Learning Model Predicting Response to Neoadjuvant Therapy for Rectal Cancer
To assess the efficacy of nCRT in LARC patients, it is crucial to consider clinical characteristics, followed by dosiomics. While T1_model, T2_model and CT_model demonstrate relatively comparable performance, each contributes unique value to the final prediction model.
Authors
- Yibao Zhang (ORCID: https://orcid.org/0000-0003-3658-0687)
- Yanye Lu (ORCID: https://orcid.org/0000-0002-3063-8051)
- Sha Li (ORCID: https://orcid.org/0000-0002-2297-9569)
- Ping Jiang (ORCID: https://orcid.org/0000-0001-8820-489X)
- Hongbin Han (ORCID: https://orcid.org/0000-0002-6988-4698)
- Zhengxian Li
- Shuai Li
Institutions
- Peking University (CN)
- Peking University Cancer Hospital (CN)
- People 's Hospital of Jilin Province (CN)
- Peking University People's Hospital (CN)
- Peking University Third Hospital (CN)
- Ministry of Education (ET)
Publication Details
- Journal
- Cancer Management and Research
- Published
- 2025-08-01
- DOI
- https://doi.org/10.2147/cmar.s517949
- Primary Topic
- Colorectal Cancer Surgical Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Peking University
- Langley Research Center
- Fundamental Research Funds for the Central Universities