Application of machine learning models to explore prognosis and cause of death in advanced intrahepatic cholangiocarcinoma patients undergoing chemotherapy
CT has improved the therapeutic efficacy of advanced ICC without significantly increasing other CODs. Furthermore, the analysis of various features using machine learning models has confirmed that the random forest model demonstrates the highest predictive performance.
Authors
- Yiqing Jiang
- Ke Su (ORCID: https://orcid.org/0000-0002-7948-6335)
- Guixiang Cao (ORCID: https://orcid.org/0009-0006-2335-8971)
- Xin Wang (ORCID: https://orcid.org/0000-0002-8694-1172)
- Jun Liu (ORCID: https://orcid.org/0000-0002-9001-9498)
- Xiaoqin Liu (ORCID: https://orcid.org/0000-0003-4519-1536)
- Qin Zeng (ORCID: https://orcid.org/0000-0002-5993-628X)
Institutions
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Affiliated Hospital of Southwest Medical University (CN)
Publication Details
- Journal
- Discover Oncology
- Published
- 2025-04-08
- DOI
- https://doi.org/10.1007/s12672-025-02274-z
- Citations
- 1
- Primary Topic
- Cholangiocarcinoma and Gallbladder Cancer Studies
- Type
- article
- Field-Weighted Citation Impact
- 2.01