Hepatology and Pancreatic Science

Department of Chronic Disease Epidemiology, University Hospital Tübingen, 72076 Tübingen, Germany

Publications

• Mini Review   
  Various Hepatorenal Syndrome Subtypes and Associated Findings as Defined by Machine Learning-based Consensus Clusters
  Author(s): Hanna Simon*
  
  Hepatorenal Syndrome (HRS) is a critical complication of advanced liver disease characterized by the development of acute kidney injury in patients with cirrhosis. HRS is a complex condition with various clinical presentations and outcomes. The ability to categorize HRS into distinct subtypes can greatly enhance our understanding and management of the condition. In recent years, machine learning-based consensus clustering has emerged as a promising approach to identify HRS subtypes and uncover associated findings. This article delves into the various hepatorenal syndrome subtypes identified through machine learning techniques, exploring their clinical significance, treatment implications, and the potential for improved patient care... Read More»
  DOI: 10.37421/2573-4563.2023.7.245

  Abstract HTML PDF