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

Author:

Reiniš Jiří,Petrenko OleksandrORCID,Simbrunner Benedikt,Hofer Benedikt S.ORCID,Schepis FilippoORCID,Scoppettuolo Marco,Saltini Dario,Indulti FedericaORCID,Guasconi TomasORCID,Albillos AgustinORCID,Téllez Luis,Villanueva Càndid,Brujats AnnaORCID,Garcia-Pagan Juan CarlosORCID,Perez-Campuzano ValeriaORCID,Hernández-Gea Virginia,Rautou Pierre-EmmanuelORCID,Moga LucileORCID,Vanwolleghem Thomas,Kwanten Wilhelmus J.ORCID,Francque SvenORCID,Trebicka JonelORCID,Gu Wenyi,Ferstl Philip G.,Gluud Lise Lotte,Bendtsen Flemming,Møller Søren,Kubicek Stefan,Mandorfer MattiasORCID,Reiberger ThomasORCID

Publisher

Elsevier BV

Subject

Hepatology

Reference28 articles.

1. Burden of liver disease in Europe: epidemiology and analysis of risk factors to identify prevention policies;Pimpin;J Hepatol,2018

2. Natural history and prognostic indicators of survival in cirrhosis: a systematic review of 118 studies;D’Amico;J Hepatol,2006

3. Hepatic venous pressure gradient predicts clinical decompensation in patients with compensated cirrhosis;Ripoll;Gastroenterology,2007

4. Baveno vii - renewing consensus in portal hypertension;de Franchis;J Hepatol,2021

5. Measurement of the hepatic venous pressure gradient and transjugular liver biopsy;Reiberger;J Vis Exp,2020

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