Development and validation of a small-sample machine learning model to predict 5–year overall survival in patients with hepatocellular carcinoma
The SVM model could predict the 5-year OS in HCC with good recognition ability and achieves significantly greater accuracy compared to traditional models. Diagnosis and treatment could be utilized to intervene in the risk factors in this model, thereby improving patient prognosis.
Authors
- Shanjun Mao (ORCID: https://orcid.org/0000-0001-9212-4761)
- Tingting Jiang (ORCID: https://orcid.org/0000-0001-8755-2147)
- Hepei Li
- Xingyu Liu (ORCID: https://orcid.org/0009-0003-3815-4953)
- Xiang Yan
- Wencan He (ORCID: https://orcid.org/0000-0003-4185-5200)
- Qian Yu (ORCID: https://orcid.org/0009-0009-2185-1887)
Institutions
- Central South University (CN)
- Hunan University (CN)
- Sichuan University (CN)
- West China Hospital of Sichuan University (CN)
- Institute of Micro and Nanotechnology (ES)
- Sichuan Cancer Hospital (CN)
- Universidad Autónoma de Madrid (ES)
Publication Details
- Journal
- BMC Cancer
- Published
- 2025-07-01
- DOI
- https://doi.org/10.1186/s12885-025-14425-0
- Citations
- 4
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 5.44
Funders
- National Natural Science Foundation of China