Publication Name	Artificial Intelligence in Medical Imaging
Manuscript ID	125894
DOI	10.35711/aimi.125894
Country	Egypt

Category	Gastroenterology & Hepatology
Manuscript Type	Systematic Reviews
Article Title	Artificial intelligence imaging for metabolic dysfunction-associated steatotic liver disease: Systematic review, meta-analysis, and treatment-response evidence assessment
Manuscript Source	Unsolicited Manuscript
All Author List	Ahmed Salman and Mohamed AbdAlla Salman
Funding Agency and Grant Number
Corresponding Author	Ahmed Salman, FRACP, FRCP, Department of Internal Medicine, Kasr Alainy School of Medicine, 1 Al-Saray Street, Al-Manial, Cairo 3178, Al Qāhirah, Egypt. awea844@gmail.com
Key Words	Metabolic dysfunction-associated steatotic liver disease; Artificial intelligence; Liver fibrosis; Hepatic steatosis; Magnetic resonance imaging; Elastography
Core Tip	Imaging artificial intelligence has been studied far more often for cross-sectional steatosis than for fibrosis or treatment monitoring. Only three independent cohorts shared the same magnetic resonance imaging (MRI) proton density fat fraction ≥ 5% steatosis target; their high summary area under the curve had a very imprecise interval and unstable prediction range. Fibrosis targets were too heterogeneous to pool. One phase 2 trial analysis used serial MRI signatures to distinguish treatment-dose groups over 12 weeks, but it did not establish an externally validated patient-level response endpoint.
Citation	Salman A, Salman MA. Artificial intelligence imaging for metabolic dysfunction-associated steatotic liver disease: Systematic review, meta-analysis, and treatment-response evidence assessment. Artif Intell Med Imaging 2026; In press DOI: https://doi.org/10.35711/aimi.125894
PDF	125894-in-press.pdf

Received	2026-07-20 06:24
Peer-Review Started	2026-07-20 06:25
First Decision by Editorial Office Director
Return for Revision	2026-08-06 08:28
Revised	2026-08-14 11:03
Publication Fee Transferred
Second Decision by Editor	2026-09-20 02:51
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-09-20 11:00
Articles in Press	2026-09-20 11:00
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	2644-3260 (online)
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: http://creativecommons.org/licenses/by-nc/4.0/
Copyright	©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc.
Permissions	For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
Publisher	Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website	http://www.wjgnet.com