Development and Internal Multicenter Validation of a Deep Learning Model for Predicting Post-Hepatectomy Liver Failure in Patients with Hepatocellular Carcinoma: A Multicenter Study
The deep learning model provides improved predictive performance for post-hepatectomy liver failure compared with logistic regression in an internally validated multicenter cohort and may support perioperative risk stratification and surgical planning.
Authors
- Xulin Liu
- Zhenheng Wu
- Jing Ying Yan (ORCID: https://orcid.org/0000-0001-8265-6270)
- Zheng Huang (ORCID: https://orcid.org/0000-0001-5143-5192)
- Feng Xia
- Zhancheng Qiu
- Bin Guo
- Qian Chen
- Qiao Zhang
- Zhicheng Liu
- Chang Shu
- Xiaoping Chen
- Bixiang Zhang
- Peng Zhu
Institutions
- Fujian Medical University (CN)
- Sichuan University (CN)
- West China Hospital of Sichuan University (CN)
- Zhongshan People's Hospital (CN)
- Zhongshan Hospital (CN)
- First Affiliated Hospital of Shihezi University Medical College (CN)
- Central Hospital of Wuhan (CN)
- Wuhan General Hospital of Guangzhou (CN)
- Second Affiliated Hospital of Zhejiang University (CN)
- Tongji Hospital (CN)
- Union Hospital (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- Cancers
- Published
- 2026-03-12
- DOI
- https://doi.org/10.3390/cancers18060926
- Primary Topic
- Hepatocellular Carcinoma Treatment and Prognosis
- Type
- article
- Field-Weighted Citation Impact
- 0.00