Prognostic prediction models for postoperative patients with stage I to III colorectal cancer based on machine learning
We constructed a comprehensive, high-accuracy, important variable-based ML architecture for predicting the 3-category survival times. This architecture could serve as a vital reference for managing CRC patients.
Authors
- Xiaolin Ji
- Shuo Xu
- Liping Duan (ORCID: https://orcid.org/0000-0001-6886-6888)
- Yingjie Guo (ORCID: https://orcid.org/0000-0003-2909-9887)
- Xiaoyu Li (ORCID: https://orcid.org/0000-0001-6778-7862)
- Zibin Tian (ORCID: https://orcid.org/0000-0002-3050-0327)
- Jinhuan Xu (ORCID: https://orcid.org/0000-0002-4344-6913)
- Renqiang Han
Institutions
- Qingdao University (CN)
- Qilu University of Technology (CN)
- Shandong Institute of Automation (CN)
- Affiliated Hospital of Qingdao University (CN)
- Shandong Academy of Sciences (CN)
Publication Details
- Journal
- World Journal of Gastrointestinal Oncology
- Published
- 2024-11-08
- DOI
- https://doi.org/10.4251/wjgo.v16.i12.4597
- Citations
- 2
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.81