Stratified mortality prediction of patients with acute kidney injury in critical care Academic Article uri icon

Overview

MeSH Major

  • Acute Kidney Injury

abstract

  • Acute Kidney Injury (AKI) is the most common cause of organ dysfunction in critically ill adults and prior studies have shown AKI is associated with a significant increase of the mortality risk. Early prediction of the mortality risk for AKI patients can help clinical decision makers better understand the patient condition in time and take appropriate actions. However, AKI is a heterogeneous disease and its cause is complex, which makes such predictions a challenging task. In this paper, we investigate machine learning models for predicting the mortality risk of AKI patients who are stratified according to their AKI stages. With this setup we demonstrate the stratified mortality prediction performance of patients with AKI is better than the results obtained on the mixed population.

publication date

  • August 21, 2019

Research

keywords

  • Academic Article

Identity

Language

  • eng

Digital Object Identifier (DOI)

  • 10.3233/SHTI190264

PubMed ID

  • 31437966

Additional Document Info

start page

  • 462

end page

  • 466

volume

  • 264