Assessment of portal hypertension severity using machine learning models in patients with compensated cirrhosis

•Models that can non-invasively assess portal hypertension severity are an unmet clinical need.•Machine learning models trained on 3/5 laboratory parameters enabled non-invasive assessment of portal hypertension severity.•These models could predict portal pressures of ≥10 mmHg or ≥16 mmHg in individuals with compensated cirrhosis.•An online tool based on these models has been made available and can be used for portal hypertension risk stratification.