A comparative study of supervised machine learning approaches to predict patient triage outcomes in hospital emergency departments-Reference-Cited by-同舟云学术

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A comparative study of supervised machine learning approaches to predict patient triage outcomes in hospital emergency departments

Published:2023-03 Issue: Volume:17 Page:100281
ISSN:2590-0056
Container-title:Array
language:en
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Author:

Elhaj Hamza^ORCID,Achour Nebil^ORCID,Tania Marzia Hoque^ORCID,Aciksari Kurtulus

Publisher

Elsevier BV

Subject

General Computer Science

Reference61 articles.

1. Building a decision support system for inpatient admission prediction with the manchester triage system and administrative check-in variables;Zlotnik;Comput Inf Nurs,2016

2. A simple tool to predict admission at the time of triage;Cameron;Emerg Med J,2015

3. Overcrowding in the nation's emergency departments: complex causes and disturbing effects;Derlet;Ann Emerg Med,2000

4. Predicting hospital admission at the emergency department triage: a novel prediction model;Parker;Am J Emerg Med,2019

5. International perspectives on emergency department crowding;Pines;Acad Emerg Med,2011

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3. Improving Patient Flow in the Emergency Rooms using Coloured Petri Nets and the ACO Algorithm;Journal of Soft Computing Paradigm;2024-06

4. Artificial Intelligence in Pediatric Emergency Medicine: Applications, Challenges, and Future Perspectives;Biomedicines;2024-05-30

5. Combining IoMT and XAI for Enhanced Triage Optimization: An MQTT Broker Approach with Contextual Recommendations for Improved Patient Priority Management in Healthcare;International Journal of Online and Biomedical Engineering (iJOE);2024-05-06

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