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
Table 3 Discrimination gains of artificial intelligence vs conventional models
| Clinical context | AI model type | AI performance | Comparator | Comparator performance | Absolute gain | Validation type |
| Atezo-Bev (advanced HCC) | Radiomic + clinical ML | AUC 0.89 (derivation), 0.75 (external) | BCLC/ALBI | 0.61/0.48 | +0.14-0.41 | Multicenter external |
| TACE | Radiomic + clinical | AUC approximately 0.79-0.81 | Clinical-only | Approximately 0.60 | +0.19-0.21 | Internal validation |
- 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