ArticleAnnals of medicine and surgery (2012)2025
AI in steatohepatitis diagnostics: precision beyond the microscope.
Article in Annals of medicine and surgery (2012), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
5 authors.
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Abstract
Non-alcoholic steatohepatitis (NASH), the progressive form of nonalcoholic fatty liver disease (NAFLD), is a major global health burden without curative therapy. Conventional histological diagnosis is limited by interobserver variability and insensitivity to subtle changes, necessitating more objective diagnostic tools. Artificial intelligence (AI), integrated with digital pathology techniques such as second harmonic generation/two-photon excitation (SHG/TPE) fluorescence imaging, provides quantitative and reproducible assessment of steatosis, ballooning, and fibrosis. Recent studies have demonstrated strong correlations between AI-derived and pathologist-assigned grades, underscoring AI's potential to enhance diagnostic precision and reproducibility. However, challenges including high operational costs, limited large-scale validation, population heterogeneity, and lack of regulatory frameworks remain barriers to clinical translation. Expanding research, developing standardized protocols, and establishing robust policies are essential for widespread adoption. AI-based pathology could revolutionize the diagnostic paradigm for liver disease, enabling earlier detection, improved patient stratification, and precision care in NASH.
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