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Artificial Intelligence in hepatology: A position paper by the Italian Association for the Study of the Liver.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver 2026

Balsano C, Alisi A, Burra P, Calvaruso V, Cammà C, Campagner A, Donatelli P, Germani G, Gerussi A, Giuffrè M, Lleo A, Panebianco V, Persico M, Pugliese N, Rossi S

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Artificial Intelligence (AI) is transforming medicine, providing unprecedented opportunities to enhance diagnosis, prognosis, and treatment across all areas of hepatology.

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APA Balsano C, Alisi A, et al. (2026). Artificial Intelligence in hepatology: A position paper by the Italian Association for the Study of the Liver.. Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver. https://doi.org/10.1016/j.dld.2026.03.005
MLA Balsano C, et al.. "Artificial Intelligence in hepatology: A position paper by the Italian Association for the Study of the Liver.." Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver, 2026.
PMID 41876274

Abstract

Artificial Intelligence (AI) is transforming medicine, providing unprecedented opportunities to enhance diagnosis, prognosis, and treatment across all areas of hepatology. This Position Paper by the Italian Association for the Study of the Liver (AISF) offers a comprehensive overview of the current and emerging roles of AI in liver diseases, highlighting both its promise and its limitations. The document critically examines methodological, ethical, and educational challenges associated with AI integration in clinical and research settings, and reviews key applications in MASLD/MASH, alcohol-related liver disease, autoimmune and cholestatic liver diseases, viral hepatitis, drug-induced liver injury, hepatocellular carcinoma, cholangiocarcinoma, and liver transplantation. Particular emphasis is placed on data quality, algorithmic fairness, explainability, and reproducibility, as well as on the necessity of robust external validation and adherence to international reporting standards (TRIPOD-AI, CONSORT-AI, DECIDE-AI, CHAMAI and others). The AISF advocates a responsible and evidence-based adoption of AI through multidisciplinary collaboration, professional education, and patient engagement. This Position Paper outlines a national roadmap to align AI innovation with ethics, transparency, and equity, ensuring that AI becomes a genuine ally of hepatology and patient-centered care.