Copyright: ©Author(s) 2026.
World J Gastroenterol. Aug 21, 2026; 32(31): 118374
Published online Aug 21, 2026. doi: 10.3748/wjg.118374
Published online Aug 21, 2026. doi: 10.3748/wjg.118374
Figure 1 Conceptual framework for risk-stratified surveillance in hepatocellular carcinoma after laparoscopic resection.
The figure illustrates the integration of clinical, tumor-related, inflammatory, and hepatic functional variables into predictive models such as least absolute shrinkage and selection operator or machine learning algorithms. Based on model outputs, patients are stratified into low-risk and high-risk groups, enabling tailored follow-up strategies and early intervention to improve clinical outcomes. LASSO: Least absolute shrinkage and selection operator; FU: Follow-up; ML: Machine learning.
- Citation: Shekar V, Lucke-Wold B. From risk stratification to precision surveillance: Interpreting early-warning models after laparoscopic resection for hepatocellular carcinoma. World J Gastroenterol 2026; 32(31): 118374
- URL: https://www.wjgnet.com/1007-9327/full/v32/i31/118374.htm
- DOI: https://dx.doi.org/10.3748/wjg.118374