Copyright: ©Author(s) 2026.
Artif Intell Gastroenterol. Aug 8, 2026; 7(2): 120311
Published online Aug 8, 2026. doi: 10.35712/aig.120311
Published online Aug 8, 2026. doi: 10.35712/aig.120311
Figure 1 Values represent reported discrimination metrics from individual retrospective studies and are not pooled estimates.
Error bars were not included due to inconsistent reporting of variance measures across the included studies. ML: Machine learning; ALBI: Albumin-bilirubin; BCLC: Barcelona Clinic Liver Cancer.
Figure 2
The framework illustrates the integration of radiomic, pathomic, and clinical data, along with methodological considerations, including validation, calibration, and causal inference, for clinical translation.
- Citation: Meena BL, Behera B, Rudra OS, Sharma D. Artificial intelligence in prognostication and treatment response modeling in advanced hepatocellular carcinoma. Artif Intell Gastroenterol 2026; 7(2): 120311
- URL: https://www.wjgnet.com/2644-3236/full/v7/i2/120311.htm
- DOI: https://dx.doi.org/10.35712/aig.120311