Leveraging machine learning and rule extraction for enhanced transparency in emergency department length of stay prediction

Leveraging machine learning and rule extraction for enhanced transparency in emergency department length of stay prediction

This study aims to address the critical issue of emergency department (ED) overcrowding, which negatively affects patient outcomes, wait times, and resource efficiency. Accurate prediction of ED length of stay (LOS) can streamline operations and improve care delivery. We utilized the MIMIC IV-ED dat...

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Main Authors: Waqar A. Sulaiman, Charithea Stylianides, Andria Nikolaou, Zinonas Antoniou, Ioannis Constantinou, Lakis Palazis, Anna Vavlitou, Theodoros Kyprianou, Efthyvoulos Kyriacou, Antonis Kakas, Marios S. Pattichis, Andreas S. Panayides, Constantinos S. Pattichis
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-02-01
Series:Frontiers in Digital Health
Subjects:
emergency department
length of stay
machine learning
gradient boosting
rule extraction
predictive modeling
Online Access:https://www.frontiersin.org/articles/10.3389/fdgth.2024.1498939/full
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https://www.frontiersin.org/articles/10.3389/fdgth.2024.1498939/full

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