Prediction of Early Recurrence in Intrahepatic Cholangiocarcinoma by Interpretable Machine Learning Model
The XGBoost model for predicting early recurrence of ICC demonstrates accuracy and reliability. Explainable machine learning models, which balance transparency and accuracy.
Authors
- Yongyi Zeng (ORCID: https://orcid.org/0000-0001-7441-4271)
- W. P. Zhou
- Jingdong LI
- Kun Yu (ORCID: https://orcid.org/0009-0004-5623-6431)
- Tingfeng Huang
- Qizhu Lin
- Shichuan Tang
Institutions
- Fujian Medical University (CN)
- Second Military Medical University (CN)
- Affiliated Hospital of North Sichuan Medical College (CN)
- Mengchao Hepatobiliary Hospital (CN)
- First Affiliated Hospital of Fujian Medical University (CN)
- Eastern Hepatobiliary Surgery Hospital (CN)
Publication Details
- Journal
- Journal of Clinical Gastroenterology
- Published
- 2025-12-22
- DOI
- https://doi.org/10.1097/mcg.0000000000002307
- Citations
- 1
- Primary Topic
- Cholangiocarcinoma and Gallbladder Cancer Studies
- Type
- article
- Field-Weighted Citation Impact
- 2.01