Development and validation of machine learning models for distant metastasis of primary hepatic carcinoma: a population-based study
We successfully constructed and validated optimal models for predicting PLCDM and its prognosis. These models provide valuable tools to guide clinical decision-making for PLCDM.
Authors
- Yongbin Zheng (ORCID: https://orcid.org/0000-0002-4227-7599)
- Dan Song (ORCID: https://orcid.org/0000-0002-8764-7610)
- Leqing Zhang
- Cong Lu
- Chenhong Wang (ORCID: https://orcid.org/0000-0003-0336-9279)
- Jingjing Miao (ORCID: https://orcid.org/0000-0001-6030-8494)
- Ying He (ORCID: https://orcid.org/0009-0004-2893-7601)
- Lun Wu (ORCID: https://orcid.org/0000-0002-8618-2049)
- Wei Wang (ORCID: https://orcid.org/0000-0001-7510-4750)
- C. Chen (ORCID: https://orcid.org/0009-0006-9792-8324)
Institutions
- Hubei University of Medicine (CN)
- Wuhan University (CN)
- China National Pharmaceutical Group Corporation (China) (CN)
- Renmin Hospital of Wuhan University (CN)
- Dongfeng General Hospital (CN)
Publication Details
- Journal
- Discover Oncology
- Published
- 2025-06-16
- DOI
- https://doi.org/10.1007/s12672-025-02894-5
- Citations
- 1
- Primary Topic
- Hepatocellular Carcinoma Treatment and Prognosis
- Type
- article
- Field-Weighted Citation Impact
- 1.32