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©The Author(s) 2026. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Jan 14, 2026; 32(2): 113059
Published online Jan 14, 2026. doi: 10.3748/wjg.v32.i2.113059
Published online Jan 14, 2026. doi: 10.3748/wjg.v32.i2.113059
Harnessing artificial intelligence for the assessment of liver fibrosis and steatosis via multiparametric ultrasound
Nicholas Viceconti, Silvia Andaloro, Mattia Paratore, Sara Miliani, Giulia D’Acunzo, Giuseppe Cerniglia, Fabrizio Mancuso, Elena Melita, Laura Riccardi, Matteo Garcovich, Department of Medical and Surgical Sciences, Diagnostic and Interventional Ultrasound Unit, CEMAD Digestive Disease Center, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome 00168, Italy
Antonio Gasbarrini, Department of Medical and Surgical Sciences, Internal Medicine and Gastroenterology Unit, CEMAD Digestive Disease Center, Fondazione Policlinico Univer
Antonio Gasbarrini, Department of Translational Medicine and Surgery, Catholic University of the Sacred Heart, Fondazione Policlinico Universitario Gemelli IRCCS, Rome 00168, Italy
Co-first authors: Nicholas Viceconti and Silvia Andaloro.
Author contributions: Viceconti N and Andaloro S contributed equally to this work in conceptualizing, designing and writing the first draft; Paratore M, Riccardi L and Garcovich M conceptualized, designed, supervised and made critical revisions; Viceconti N, Andaloro S, Paratore M, Miliani S, D’Acunzo G, Cerniglia G, Mancuso F, Melita E, Gasbarrini A, Riccardi L, and Garcovich M prepared the draft and approved the submitted version.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Mattia Paratore, MD, Doctor, Department of Medical and Surgical Sciences, Diagnostic and Interventional Ultrasound Unit, CEMAD Digestive Disease Center, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Largo Agostino Gemelli, 8, Rome 00168, Italy. mattia.paratore@guest.policlinicogemelli.it
Received: August 14, 2025
Revised: November 4, 2025
Accepted: December 2, 2025
Published online: January 14, 2026
Processing time: 151 Days and 17.6 Hours
Revised: November 4, 2025
Accepted: December 2, 2025
Published online: January 14, 2026
Processing time: 151 Days and 17.6 Hours
Core Tip
Core Tip: The emergence of artificial intelligence has led to its application across various fields, including hepatology and medical imaging. Its enormous potential has already been recognized and documented in numerous studies. This review explores the current application and future potential of artificial intelligence in ultrasound imaging, emphasizing its role in chronic liver disease early diagnosis and follow-up.