Machine learning predicts post-transplant muscle loss in hepatocellular carcinoma patients without sarcopenia
A highly efficient model based on machine learning was developed to predict postoperative muscle loss in hepatocellular carcinoma patients undergoing liver transplantation, providing a valuable reference for the early detection of adverse events following the procedure.
Authors
- Huigang Li (ORCID: https://orcid.org/0000-0002-5575-8068)
- Zuyuan Lin
- Xiao‐Ming Xu (ORCID: https://orcid.org/0000-0002-7229-0081)
- Di Lü (ORCID: https://orcid.org/0000-0001-5716-8451)
- Renyi Su (ORCID: https://orcid.org/0000-0001-9577-7012)
- Chiyu He (ORCID: https://orcid.org/0000-0002-1794-2876)
- Jinyan Chen (ORCID: https://orcid.org/0000-0003-4103-7056)
- Shuhan Jiang (ORCID: https://orcid.org/0000-0003-3370-3565)
- Xuyong Wei (ORCID: https://orcid.org/0000-0001-8755-5268)
- Jianyong Zhuo
- Zhigang Hu (ORCID: https://orcid.org/0000-0002-4482-1535)
- Ruijie Zhao (ORCID: https://orcid.org/0000-0003-2204-7996)
- Weiliang Shen (ORCID: https://orcid.org/0000-0001-8131-325X)
- Y. Nancy You (ORCID: https://orcid.org/0000-0002-5294-288X)
- Shusen Zheng
Institutions
- Blood Center of Zhejiang Province (CN)
- Zhejiang Shuren University (CN)
- Zhejiang Provincial People's Hospital (CN)
- Affiliated Hangzhou First People's Hospital, Westlake University, School of Medicine (CN)
- Zhejiang University-University of Edinburgh Institute (CN)
- Ministry of Public Health (MG)
- Hangzhou Medical College (CN)
- First Affiliated Hospital Zhejiang University (CN)
- Zhejiang University (CN)
Publication Details
- Journal
- BMC Cancer
- Published
- 2025-10-14
- DOI
- https://doi.org/10.1186/s12885-025-14973-5
- Citations
- 2
- Primary Topic
- Nutrition and Health in Aging
- Type
- article
- Field-Weighted Citation Impact
- 2.33
Funders
- National Natural Science Foundation of China
- Major Research Plan
- National Key Research and Development Program of China