+ HEALTH Advanced navigation techniques in image-guided interventions and surgical robotics require the rapid and prec…+ HEALTH Introduction Metabolic dysfunction-associated steatohepatitis (MASH) is one of the most common liver diseases…+ SCIENCE Background Decoding the genetic code to unveil its genome functionality is a monumental task which would grea…+ HEALTH Background Several gene expression signatures (GESs) are used for risk stratification in estrogen receptor-po…± HEALTH Background Artificial intelligence-powered large language models (LLMs) are increasingly used by patients see…+ HEALTH In-depth characterization of pathological protein aggregate with its subcomponents is pivotal for early diagn…+ SCIENCE Descriptors link basic physicochemical parameters that characterize the materials and the environment to the…+ HEALTH Background Reflux esophagitis (RE) is a common gastroesophageal disorder among candidates for metabolic baria…
TruaceTracing the truth around AIFriday, September 18, 2026
Subscribe
Health·G Space·Evidence-backed gain·Published 2026-09-18

How to apply artificial intelligence (AI) to facilitate and enhance MASH trials

Abstract: Introduction Metabolic dysfunction-associated steatohepatitis (MASH) is one of the most common liver diseases, but thus far only two drugs (resmetirom and semaglutide) have received conditional approval for use. Successful MASH trials are thus highly desired to fill the therapeutic and evidence gap. Concurrently, AI has powered advances in multiple areas of medicine. We consider in this review the potential applications of AI to enhance MASH trials. Methods We conduct a narrative review of AI uses in MASH, with…

TRV-2026-1134Peer-reviewedPermanent record — cite & verify
How to apply artificial intelligence (AI) to facilitate and enhance MASH trials

"Respiratory bronchiolitis" by Pulmonary Pathology is licensed under CC BY-SA 2.0. To view a copy of this license, visit https://creativecommons.org/licenses/by-sa/2.0/.

The quick read

Published September 16, 2026, this narrative review examines how AI is being applied to metabolic dysfunction-associated steatohepatitis trials, a field where only resmetirom and semaglutide had received conditional approval at the time of writing.

Regulatory qualification of AI pathology models for endpoint determination signals a shift in how liver disease trials are run, but the review remains largely descriptive of potential uses, leaving open how broadly these tools improve enrollment, retention, and trial validity in practice.

Main points
  • MASH is described as one of the most common liver diseases with only two drugs having received conditional approval.
  • FDA and EMA have qualified specific AI models for endpoint determination in MASH trials.
  • Review also covers AI risk models for enrollment and large language models for patient interactions.
Gain

AI-based digital pathology models have been qualified by regulators for endpoint determination in MASH trials, with additional AI risk models and large language models applied to patient enrollment, recruitment and retention.

The rundown

The review describes digital pathology and AI technologies for MASH grading as a mature application, noting regulatory qualification for trial endpoints.

It further details contemporary AI risk models to facilitate patient enrollment and large language models to support recruitment and retention, drawing lessons from other medical domains and current guidelines.

Sources

Reader signal

How should this claim be treated?

The debate