Multitask radioclinical decision stratification in non-metastatic colon cancer: integrating MMR status, pT staging, and high-risk pathological factors
The multi-task machine learning model proposed in this study enables non-invasive and precise preoperative stratification of patients with NMCC based on MMR status, pT stage, and pathological risk factors. This predictive tool demonstrates significant potential in facilitating preoperative risk stratification and guiding individualized therapeutic strategies.
Authors
- Yu Fan (ORCID: https://orcid.org/0000-0002-7473-6104)
- Jiong Liu (ORCID: https://orcid.org/0000-0002-0501-1783)
- Runying Yang (ORCID: https://orcid.org/0000-0002-5983-9439)
- Lihong Li (ORCID: https://orcid.org/0000-0003-3977-8285)
- Yan Shu (ORCID: https://orcid.org/0000-0002-0035-5368)
- Wenzheng Wu
- Jian Shu (ORCID: https://orcid.org/0000-0002-7386-7217)
Institutions
- Southwest Medical University (CN)
- Affiliated Hospital of Southwest Medical University (CN)
Publication Details
- Journal
- Abdominal Radiology
- Published
- 2025-09-22
- DOI
- https://doi.org/10.1007/s00261-025-05195-1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Guangdong Provincial People's Hospital