Development and validation of machine learning models for predicting no. 253 lymph node metastasis in left-sided colorectal cancer using clinical and CT-based radiomic features
A clinical and CT-based radiomics model shows promise in predicting No. 253 LN metastasis in left-sided CRC and provides insights for optimizing IMA ligation strategies.
Authors
- Yong Jiang (ORCID: https://orcid.org/0000-0001-6047-3342)
- Yingchao Wu (ORCID: https://orcid.org/0000-0002-4810-0399)
- Shurong Liu (ORCID: https://orcid.org/0000-0002-5456-8828)
- Xin Wang (ORCID: https://orcid.org/0000-0002-5122-2418)
- Xiaoying Wang (ORCID: https://orcid.org/0000-0001-9822-961X)
- Kexin Wang (ORCID: https://orcid.org/0000-0001-9184-3967)
- Guowei Chen (ORCID: https://orcid.org/0000-0002-7440-5639)
- Junling Zhang
- Hongwei Zhang (ORCID: https://orcid.org/0000-0002-4211-444X)
- Xiaocong Pang (ORCID: https://orcid.org/0000-0002-6891-4701)
Institutions
- Capital Medical University (CN)
- Peking University (CN)
- Peking University First Hospital (CN)
- Beijing YouAn Hospital (CN)
Publication Details
- Journal
- Cancer Imaging
- Published
- 2025-04-29
- DOI
- https://doi.org/10.1186/s40644-025-00876-y
- Citations
- 2
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 2.72
Funders
- Peking University First Hospital
- National Natural Science Foundation of China
- Peking University