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 Article Swipe
Related Concepts
Medicine
Hepatocellular carcinoma
Hepatology
Internal medicine
Chronic hepatitis
Gastroenterology
Oncology
Immunology
Virus
Linghong Wu
,
Jennifer Liu
,
Hongyuan Huang
,
Dongmei Pan
,
Cuiping Fu
,
Lu Yao
,
Hui Zhou
,
Kaiyong Huang
,
TianRen Huang
,
Li Yang
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1186/s12876-025-03697-2
· OA: W4408333373
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1186/s12876-025-03697-2
· OA: W4408333373
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.
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