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©The Author(s) 2025.
Artif Intell Gastroenterol. Jun 8, 2025; 6(1): 107105
Published online Jun 8, 2025. doi: 10.35712/aig.v6.i1.107105
Published online Jun 8, 2025. doi: 10.35712/aig.v6.i1.107105
Table 1 Artificial intelligence applications in metabolic-associated steatotic liver disease diagnosis and treatment
Application | Description | Ref. |
AI-based pathology tools | Improve histological scoring accuracy and reduce reader variability | Pulaski et al[3], Ratziu et al[4], Solomon et al[2] |
Non-invasive screening models | Predict MASLD using lab and anthropometric data with high accuracy | Masaebi et al[5], Njei et al[6], Leow et al[10], Fan et al[7], Bosch et al[8] |
AI-enhanced ultrasonography | Enhances steatosis and fibrosis diagnosis with improved AUC values | Santoro et al[11], Fujii et al[13], Luetkens et al[12] |
Gut microbiota-based diagnosis | Identifies MASLD using ML models trained on gut microbiota data | Park et al[14] |
Personalized treatment strategies | Guide targeted interventions using clinical and risk factor data | Dabbah et al[15], Wu et al[16], Malik et al[17] |
Treatment response assessment | Evaluates therapeutic efficacy using continuous histological scores | Ratziu et al[4], Pulaski et al[3], Nishida et al[18] |
- Citation: Gao YN, Chen ML, Li WM, Liu Q, Jiao Y. Advancing the diagnosis and treatment of metabolic-associated steatotic liver disease: The transformative role of artificial intelligence. Artif Intell Gastroenterol 2025; 6(1): 107105
- URL: https://www.wjgnet.com/2644-3236/full/v6/i1/107105.htm
- DOI: https://dx.doi.org/10.35712/aig.v6.i1.107105