AI-Based Models for Risk Prediction in MASLD: A Systematic Review

Chen C, Liang J, Ma F, Glass L, Sun J, Xiao C. UNITE: Uncertainty-based Health Risk Prediction Leveraging Multi-sourced Data. Proceedings of the Web Conference 20212021. p. 217–26.

Than N. Metabolic Dysfunction Associated Steatotic Liver Disease (MASLD): A General Overview and Approach in Clinical Practice. Medical Research Archives. 2023;11(11).

Chrysavgis LG. Glucagon-Like Peptide 1, Glucose-Dependent Insulinotropic Polypeptide, and Glucagon Receptor Agonists in Metabolic Dysfunction-Associated Steatotic Liver Disease: Novel Medication in New Liver Disease Nomenclature. International Journal of Molecular Sciences. 2024;25:3832.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Targher G, Tilg H, Byrne CD. Non-Alcoholic Fatty Liver Disease: A Multisystem Disease Requiring a Multidisciplinary and Holistic Approach. The Lancet Gastroenterology & Hepatology. 2021;6:578–588.

Article  Google Scholar 

Wang Y. Pharmacological Therapy of Metabolic Dysfunction-Associated Steatotic Liver Disease-Driven Hepatocellular Carcinoma. Frontiers in Pharmacology. 2024;14:1336216.

Article  PubMed  PubMed Central  Google Scholar 

Bai Y. Activation of AMPK Pathway by Low-dose Donafenib and Atorvastatin Combination Improves High-fat Diet-induced Metabolic Dysfunction-associated Steatotic Liver Disease. Molecular Medicine Reports. 2024;29:51.

Article  CAS  PubMed  Google Scholar 

Shiraishi S. A New Non-Obese Steatohepatitis Mouse Model With Cardiac Dysfunction Induced by Addition of Ethanol to a High-Fat/High-Cholesterol Diet. Biology. 2024;13:91.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Song R. Comparison of NAFLD, MAFLD, MASLD and Pure-Masld Characteristics and Mortality Outcomes in United States Adults. 2023.

Kim D. Steatotic Liver Disease-associated All-cause/Cause-specific Mortality in the United States. Alimentary Pharmacology & Therapeutics. 2024;60:33–42.

Article  Google Scholar 

Saini A, Meitei AJ, Singh J. Machine Learning in Healthcare: A Review. SSRN Electronic Journal. 2021.

Xu F. Effect of AI Deep Learning Techniques on Possible Complications and Clinical Nursing Quality of Patients With Coronary Heart Disease. Food Science and Technology. 2022;42.

Liao Z, Lan P, Fan X, Kelly B, Innes AQ, Liao Z. SIRVD-DL: A COVID-19 Deep Learning Prediction Model Based on Time-Dependent SIRVD. Computers in Biology and Medicine. 2021;138:104868.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zargoush M, Sameh A, Javadi M, Shabani S, Ghazalbash S, Perri D. The Impact of Recency and Adequacy of Historical Information on Sepsis Predictions Using Machine Learning. Scientific Reports. 2021;11(1).

Mantovani A, Csermely A, Petracca G et al. Non-Alcoholic Fatty Liver Disease and Risk of Fatal and Non-Fatal Cardiovascular Events: An Updated Systematic Review and Meta-Analysis. The Lancet Gastroenterology & Hepatology. 2021;6:903–913.

Article  Google Scholar 

Tamaki N. Long-term Clinical Outcomes in Steatotic Liver Disease and Incidence of Liver-related Events, Cardiovascular Events and All-cause Mortality. Alimentary Pharmacology & Therapeutics. 2024;60:61–69.

Article  CAS  Google Scholar 

Naqvi IH, Talib A, Mahmood K, Abidi R, Rizvi SNZ. The Ability of the New ALBI Scoring in Predicting Mortality, Complications and Prognostic Comparison Among Cirrhotics. Gastroenterology Review. 2019;14:250–257.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhao X, Ou Y-Y, Guo D, Che X-Q, Li Z-Q. Evaluation of the Prognostic Value of Existing Scoring Systems for Nosocomial Infection in Patients With Decompensated Liver Cirrhosis. The Turkish Journal of Gastroenterology. 2023;34:43–52.

Article  PubMed  PubMed Central  Google Scholar 

Stefan N. Effect of Essential Phospholipids on Hepatic Steatosis in Metabolic Dysfunction-Associated Steatotic Liver Disease Associated With Type 2 Diabetes Mellitus and/or Hyperlipidemia and/or Obesity: Study Protocol of a Randomized, Double-Blind, Phase IV Clinical Trial. Trials. 2024;25:374.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Hardy TL, McPherson S. Imaging-Based Assessment of Steatosis, Inflammation and Fibrosis in NAFLD. Current Hepatology Reports. 2017;16:298–307.

Article  Google Scholar 

Tas E. Diagnostic Accuracy of Transient Elastography in Hepatosteatosis in Youth With Obesity. Journal of the Endocrine Society. 2024;8:bvae110.

Article  PubMed  PubMed Central  Google Scholar 

Kang DE. Association Between Alcohol Consumption and Metabolic Dysfunction-Associated Steatotic Liver Disease Based on Alcohol Flushing Response in Men: The Korea National Health and Nutrition Examination Survey 2019–2021. Nutrients. 2023;15:3901.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Batra N. Accuracy of Chronic Liver Failure Consortium (CLIF-C) ACLF Score Compared With Meld, MELD-NA and CTP as a Mortality Predictor in Acute on Chronic Liver Failure Patients Admitted to Tertiary Rural Care Hospital. F1000research. 2024;13:419.

Article  Google Scholar 

Zhang S, Mak LY, Yuen MF, Seto WK. Screening Strategy for Non-Alcoholic Fatty Liver Disease. Clinical and Molecular Hepatology. 2023;29:S103–S122.

Article  PubMed  Google Scholar 

Kobayashi T. Prediction of Outcomes in Patients With Metabolic Dysfunction-Associated Steatotic Liver Disease Based on Initial Measurements and Subsequent Changes in Magnetic Resonance Elastography. Journal of Gastroenterology. 2023;59:56–65.

Article  PubMed  PubMed Central  Google Scholar 

Schneider CV. Prevalence of At-risk <scp>MASH</Scp>, <scp>M</Scp>et<scp>ALD</Scp> and Alcohol-associated Steatotic Liver Disease in the General Population. Alimentary Pharmacology & Therapeutics. 2024;59:1271–1281.

Article  CAS  Google Scholar 

Decharatanachart P, Chaiteerakij R, Tiyarattanachai T, Treeprasertsuk S. Application of artificial intelligence in non-alcoholic fatty liver disease and liver fibrosis: a systematic review and meta-analysis. Therap Adv Gastroenterol. 2021;14:17562848211062808.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Charu V, Liang JW, Mannalithara A, Kwong A, Tian L, Kim WR. Benchmarking clinical risk prediction algorithms with ensemble machine learning for the noninvasive diagnosis of liver fibrosis in NAFLD. Hepatology. 2024. https://doi.org/10.1097/HEP.0000000000000908.

Article  PubMed  Google Scholar 

Dunn W, Alkhouri N, Yip TC, et al. Su1537 MACHINE LEARNING ADVANCED FIBROSIS AND AT-RISK MASH (ALADDIN) WITH A WEB-BASED CALCULATOR FOR PROBABILITY PREDICTION. Gastroenterology. 2024;166(5).

Alkhouri N, Yip TC-F, Castera L, et al. Aladdin: A machine learning approach to enhance the prediction of significant fibrosis or higher in masld. Official journal of the American College of Gastroenterology| ACG. 2022:10.14309.

Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan—a web and mobile app for systematic reviews. Systematic reviews. 2016;5:1–10.

Article  Google Scholar 

Whiting PF, Rutjes AW, Westwood ME et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Annals of internal medicine. 2011;155:529–536.

Article  PubMed  Google Scholar 

McGlinchey A, Geng D, Govaere O et al. Metabolomics approaches to identify biomarkers of non-alcoholic fatty liver disease. Journal of Hepatology. 2020. https://doi.org/10.1016/s0168-8278(20)31357-x.

Article  Google Scholar 

Lee J, Westphal M, Vali Y et al. Machine learning algorithm improves the detection of NASH (NAS-based) and at-risk NASH: A development and validation study. Hepatology. 2023;78:258–271.

Article  PubMed  Google Scholar 

Farzi M, McGenity C, Cratchley A, et al. Liver-Quant: Feature-Based Image Analysis Toolkit for Automatic Quantification of Metabolic Dysfunction-Associated Steatotic Liver Disease. medRxiv. 2024:2024.05. 21.24305727.

Stefanakis K, Mingrone G, George J, Mantzoros CS. Accurate non-invasive detection of MASH with fibrosis F2–F3 using a lightweight machine learning model with minimal clinical and metabolomic variables. Metabolism. 2025;163:156082.

Article  CAS  PubMed  Google Scholar 

Fan R, Yu N, Li G et al. Machine-learning model comprising five clinical indices and liver stiffness measurement can accurately identify MASLD-related liver fibrosis. Liver Int. 2024;44:749–759.

Article  PubMed  Google Scholar 

Njei B, Osta E, Njei N, Al-Ajlouni YA, Lim JK. An explainable machine learning model for prediction of high-risk nonalcoholic steatohepatitis. Scientific Reports. 2024;14:8589.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Leow YW, Chan WL, Lai LL et al. LIVERSTAT for risk stratification for patients with metabolic dysfunction-associated fatty liver disease. Journal of Gastroenterology and Hepatology. 2024;39:2182.

Article  CAS  PubMed  Google Scholar 

NaderiYaghouti AR, Zamanian H, Shalbaf A. Machine learning approaches for early detection of non-alcoholic steatohepatitis based on clinical and blood parameters. Sci Rep. 2024;14:2442.

Article  CAS  Google Scholar 

Suarez M, Martinez R, Torres AM, Ramon A, Blasco P, Mateo J. Personalized Risk Assessment of Hepatic Fibrosis after Cholecystectomy in Metabolic-Associated Steatotic Liver Disease: A Machine Learning Approach. J Clin Med. 2023. https://doi.org/10.3390/jcm12206489.

Article 

Comments (0)

No login
gif