Study Background
- Nonalcoholic steatohepatitis (NASH) cirrhosis is characterized by heterogeneity in histology, clinical presentation, and prognosis1
- In patients with NASH, the presence of cirrhosis is associated with an increased risk of liver-related and all-cause mortality, but identification of those at risk for liver-related clinical events may be challenging2-4
- Although machine learning (ML) approaches have been used to evaluate liver histology in NASH,5,6 the utility of these approaches to characterize fibrosis and risk stratify patients with cirrhosis requires evaluation
