Translational artificial intelligence in therapeutic-era metabolic dysfunction-associated steatohepatitis: The ACTION framework

Metabolic dysfunction-associated steatohepatitis (MASH) has entered a therapeutic era in which priorities extend beyond detecting steatosis to identifying treatment-actionable fibrosis, rationalising referral and biopsy, standardising trial endpoints and monitoring response.Artificial intelligence (AI) spans electronic health records, non-invasive tests, imaging and digital pathology, but reports often omit the user, threshold and consequence.We conducted a structured narrative review and developed the authorproposed ACTION framework.ACTION comprises attached action, calibration in context, threshold-specific benefit, integration, oversight, and non-discrimination and monitoring.Evidence is uneven.Case-finding and enrichment models can identify uncoded or higher-risk patients, but their prospective effects on testing, referral and outcomes remain unproven.Imaging AI supports reproducible quantification, although signals may add little beyond clinical variables.The human-reviewed AI-based measurement tool for MASH (in regulatory records) is among the most mature applications reviewed, within a narrowly specified clinical-trial context.It is qualified for specified MASH clinical-trial workflows, not for autonomous diagnosis or unrestricted treatment selection.AI becomes clinically meaningful only when a calibrated output is linked to a predefined action, an accountable human user and a measurable patient or trial outcome.