Predicting the Risk of Decompensation in Patients with Cirrhosis – a Validated Machine Learning Approach

20260 citationsJournal Articlehybrid Open Access

Authors

Philip J Johnson · University of Liverpool

Anton Kalyuzhnyy · University of Liverpool

Arturas Grauslys · Institute of Cancer Research

Hidenori Toyoda · Ogaki Municipal Hospital

Erica Villa · University of Modena and Reggio Emilia

Omar Elshaarawy · Royal Liverpool and Broadgreen University Hospital NHS Trust

S. Stewart

Abstract

Our validated machine learning model based on readily available clinical, and laboratory features accurately quantitates the risk of liver decompensation in patients with compensated hepatic cirrhosis.

Topics & Keywords

Liver Disease and Transplantation Liver Disease Diagnosis and Treatment Hepatitis C virus research

Publication Details

Published in: The American Journal of Gastroenterology

DOI: 10.14309/ajg.0000000000004004

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Predicting the Risk of Decompensation in Patients with Cirrhosis – a Validated Machine Learning Approach

Authors

Abstract

Topics & Keywords

Publication Details