Development and validation of an interpretable machine learning model for predicting the risk of hepatocellular carcinoma in patients with chronic hepatitis B: a case-control study
ML models can be used as a tool to predict the risk of HCC in patients with CHB. The RF model has the best predictive performance and helps clinicians to identify high-risk patients and intervene early to reduce or delay the occurrence of HCC. However, the model needs to be further improved through large sample studies.
Authors
- Kaiyong Huang
- Hongyuan Huang
- Dongmei Pan
- Hui Zhou (ORCID: https://orcid.org/0000-0001-9157-3792)
- Jennifer Liu (ORCID: https://orcid.org/0000-0002-7177-9758)
- Linghong Wu
- TianRen Huang
- Cuiping Fu (ORCID: https://orcid.org/0000-0002-8805-0998)
- Li Yang (ORCID: https://orcid.org/0000-0003-2716-3793)
- Lu Yao (ORCID: https://orcid.org/0000-0002-9524-204X)
Institutions
- Guangxi Medical University (CN)
- Fourth Affiliated Hospital of Guangxi Medical University (CN)
Publication Details
- Journal
- BMC Gastroenterology
- Published
- 2025-03-11
- DOI
- https://doi.org/10.1186/s12876-025-03697-2
- Citations
- 11
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 32.31