Background/Objectives: Artificial intelligence (AI) is an emerging technology for diagnosing liver fibrosis in Metabolic-Dysfunction-Associated Steatotic Liver Disease (MASLD), but a comprehensive synthesis of its performance is lacking. This systematic review (SR) aimed to evaluate the current evidence of AI models for diagnosing or staging liver fibrosis in patients with MASLD compared to conventional diagnostic tools. Methods: A comprehensive search was conducted in PubMed, Scopus, Web of Science, ScienceDirect, Embase, LILACS, IEEE Series, and Association for Computing Machinery (ACM). Primary studies applying AI to diagnose fibrosis in adults with MASLD were included. Risk of bias was assessed using the QUADAS-2 tool, and methodological reporting was evaluated according to the MINimum Information for Medical AI Reporting (MINIMAR) guideline. A narrative synthesis was performed, grouping studies by data type (clinical/laboratory vs. imaging) and summarizing diagnostic performance and clinical application. A frequency-based analysis was applied to identify the most recurrent predictive features, and an analysis of the AI architecture and application was reported. The review was registered in PROSPERO (CRD420251035919). Results: Twenty-one studies were included, encompassing 19,221 patients and 5237 images. Across studies, AI models consistently outperformed non-invasive scores such as Fibrosis-4 Index (FIB-4) and NAFLD Fibrosis Score (NFS). The most frequent predictive variables were identified. Despite an overall low risk of bias, methodological transparency and external validation were limited. Conclusions: AI is feasible for the non-invasive diagnosis of liver fibrosis in MASLD, demonstrating superior accuracy to standard clinical scores. Broader clinical application is limited by the lack of external validation and high heterogeneity among the studies. Prospective validation in diverse, multicenter cohorts is essential before AI can be integrated into routine clinical practice.

Background and aim: Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) remains controversial regarding the impact of moderate alcohol consumption on disease progression and clinical outcomes. This systematic review aimed to evaluate the effects of moderate alcohol intake (up to 30 g/day for men and 20 g/day for women) on the development and progression of Steatotic Liver Disease (SLD), including outcomes such as histopathological progression, hepatocellular carcinoma (HCC), cardiovascular disease, and mortality. Methods: The review followed PRISMA guidelines and included longitudinal cohort studies identified through PubMed, Scopus, Web of Science, Embase, and LILACS. Nine studies were selected for qualitative analysis, and seven were included in the meta-analysis. Effect measures, Hazard Ratios (HR) and Odds Ratios (OR), were pooled using Cochrane RevMan, and study quality was assessed with the Newcastle–Ottawa Scale. PROSPERO: CRD420261277466. Results: The meta-analysis showed no statistically significant association between moderate alcohol consumption and fibrosis progression (HR: 1.63 [95% CI: 0.96–2.77]; OR: 1.44 [95% CI: 0.56–3.72]). However, a statistically significant protective association was observed for all-cause mortality (HR: 0.73 [95% CI: 0.62–0.86]). High heterogeneity was noted across studies (I ² = 56.9–86.2%). Excessive alcohol consumption remained a strong risk factor for adverse outcomes, and the incidence of HCC significantly increased among patients with advanced fibrosis, even with light alcohol intake. Conclusions: Even moderate alcohol consumption may contribute to the progression of severe hepatic outcomes in SLD. These findings support clinical recommendations for total abstinence, particularly in patients with established fibrosis, to prevent progression to cirrhosis and hepatocellular carcinoma.