Artificial intelligence applications for managing metabolic dysfunction-associated steatotic liver disease - Current status and future prospects

Sep 28, 2026

The incidence and prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) have continued to increase, making it a leading chronic liver condition worldwide. MASLD is highly comorbid with obesity, type 2 diabetes, cardiovascular disease, and chronic kidney disease, creating substantial medical and socioeconomic burden. Although research has advanced, clinical practice still struggles with early screening, risk stratification, prognostic prediction, and long-term therapeutic monitoring, where artificial intelligence can support earlier, more accurate, and more individualized care.

LanguageEnglish

CategoryHealthcare

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Pages10

Reading Time25 min

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Introduction

| W | J | G | World Journal of
Gastroenterology | | --- | --- | --- | --- | Submit a Manuscript: [https://www.f6publishing.com](https://www.f6publishing.com) World J Gastroenterol 2025 December 21; 31(47): 111900 DOI: 10.3748/wjg.v31.i47.111900 ISSN 1007-9327 (print) ISSN 2219-2840 (online) MINIREVIEWS Artificial intelligence applications for managing metabolic dysfunction-associated steatotic liver disease: Current status and future prospects Jian-Jun Lou, Jing Zeng Specialty type: Gastroenterology and hepatology Provenance and peer review: Invited article; Externally peer reviewed. Peer-review model: Single blind Peer-review report’s classification Scientific Quality: Grade B, Grade B Novelty: Grade B, Grade C Creativity or Innovation: Grade B, Grade B Scientific Significance: Grade B, Grade B P-Reviewer: Greco S, MD, Italy; van Kleef LA, MD, PhD, Postdoctoral Fellow, Netherlands Received: July 14, 2025 Revised: October 7, 2025 Accepted: November 5, 2025 Published online: December 21, 2025 Processing time: 160 Days and 17.9 Hours Jian-Jun Lou, Chronic Liver Disease Center, The Affiliated Yangming Hospital of Ningbo University (Yuyao People's Hospital), Ningbo 315400, Zhejiang Province, China Jing Zeng, Department of Gastroenterology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China Corresponding author: Jing Zeng, MD, Department of Gastroenterology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, No. 1665 Kongjiang Road, Shanghai 200092, [China.](China. zjupup@126.com)[ zjupup@126.com](China. zjupup@126.com) Abstract The incidence and prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) have continued to increase in recent years, making it one of the most common chronic liver diseases worldwide. MASLD is highly comorbid with obesity, type 2 diabetes, cardiovascular disease, and chronic kidney disease, posing a serious threat to public health and creating a significant medical and socioeconomic burden. Despite advances in research, current clinical practice still faces considerable challenges in early screening, risk stratification, prognostic prediction, and long-term therapeutic monitoring. Recent advances in artificial intelligence (AI) have provided transformative opportunities to address these challenges. AI has demonstrated unique advantages in imaging interpretation, multiomics integration, electronic health record analysis, and remote health management, significantly improving the accuracy and efficiency of the noninvasive diagnosis, individualized risk stratification, precision therapy, and dynamic disease monitoring of MASLD. In this mini-review, the latest advances in AI applications for MASLD diagnosis and management are systematically summarized, and a forward-looking perspective on the role of AI in enabling the next generation of smart health care systems for MASLD is offered, with the aim of providing theoretical and practical guidance for the clinical management of this disease. Key Words: Metabolic dysfunction-associated steatotic liver disease; Artificial intelligence; Multiomics integration; Early screening; Risk stratification; Disease monitoring; Machine learning; Clinical decision support WJG [https://www.wjgnet.com](https://www.wjgnet.com) 1 December 21, 2025 Volume 31 Issue 47 Lou JJ et al. AI in MASLD ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved. Core Tip: Artificial intelligence (AI) is rapidly advancing the management of metabolic dysfunction-associated steatotic liver disease (MASLD) . Because AI can integrate imaging, multiomics, and electronic health record data, the use of AI enables earlier diagnosis, more accurate risk stratification, and personalized treatment. This mini-review summarizes recent progress and future directions for applying AI to improve MASLD care and outcomes. Citation: Lou JJ, Zeng

FAQs

What makes MASLD a major public health concern?

MASLD incidence and prevalence keep rising worldwide. It is highly comorbid with obesity, type 2 diabetes, cardiovascular disease, and chronic kidney disease, increasing medical and socioeconomic burden.

Which clinical problems are still challenging in MASLD management?

Current practice faces major difficulties in early screening, risk stratification, prognostic prediction, and long-term therapeutic monitoring.

How can artificial intelligence help in MASLD diagnosis and management?

AI can improve imaging interpretation, multiomics integration, electronic health record analysis, and remote health management. It supports earlier noninvasive diagnosis, more accurate risk stratification, precision therapy, and dynamic disease monitoring.

Sep 28, 2026

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