Rule-Based Models for Risk Estimation and Analysis of In-hospital Mortality in Emergency and Critical Care

Rule-Based Models for Risk Estimation and Analysis of In-hospital Mortality in Emergency and Critical Care

We propose a novel method that uses associative classification and odds ratios to predict in-hospital mortality in emergency and critical care. Manual mortality risk scores have previously been used to assess the care needed for each patient and their need for palliative measures. Automated approach...

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Bibliographic Details
Main Authors: Oliver Haas, Andreas Maier, Eva Rothgang
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-11-01
Series:Frontiers in Medicine
Subjects:
in-hospital mortality
critical care
odds ratio
associative classification
machine learning
artificial intelligence
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2021.785711/full

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