Supporting clinical decision making in the emergency department for paediatric patients using machine learning - A scoping review protocol

Aug 4, 2026

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Machine learning can function as a clinical decision support system to help clinicians make fast, accurate medical decisions in emergency departments. This scoping review protocol aims to identify and summarise existing research on machine learning CDSS tools, with emphasis on models suitable for paediatric patients where gaps in current knowledge persist. The review will follow Arksey and O’Malley’s scoping framework with additional guidelines, selecting studies from the last five years.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages13

Reading Time33 min

AccessFree to download

Abstract

Introduction

Materials and methods

Discussion

Technological University Dublin ARROW@TU Dublin | Articles | School of Computer Science | | --- | --- | | 2023
Supporting clinical decision making in the emergency department for paediatric patients using machine learning: A scoping review protocol
Fiona Leonard
Technological University Dublin
Dympna O. Sullivan
Technological University Dublin
John Gilligan
Technological University Dublin See next page for additional authors
Follow this and additional works at: [https://arrow.tudublin.ie/scschcomart](https://arrow.tudublin.ie/scschcomart) | | Recommended Citation Leonard, F., Sullivan, D. O., Gilligan, J., Shea, N. O., & Barrett, M. J. (2023) . Supporting clinical decision making in the emergency department for paediatric patients using machine learning. PLoS ONE, 18(11 November), Article e0294231 . [https://doi.org/10.1371/journal.pone.0294231](https://doi.org/10.1371/journal.pone.0294231) This Article is brought to you for free and open access by the School of Computer Science at ARROW@TU Dublin. It has been accepted for inclusion in Articles by an authorized administrator of ARROW@TU Dublin. For more information, [please contact vera.ki](please contact vera.ki)[lshaw@tudublin.ie](lshaw@tudublin.ie). This work is licensed under a Creative Commons Attribution 4.0 International License. Authors Fiona Leonard, Dympna O. Sullivan, John Gilligan, Nicola O. Shea, and Michael J. Barrett This article is available at ARROW@TU Dublin: [https://arrow.tudublin.ie/scschcomart/253](https://arrow.tudublin.ie/scschcomart/253) PLOS ONE OPEN ACCESS Citation: Leonard F, O’Sullivan D, Gilligan J, O’Shea N, Barrett MJ (2023) Supporting clinical decision making in the emergency department for paediatric patients using machine learning: A scoping review protocol. PLoS ONE 18(11): e0294231 . [https://doi](https://doi). org/10 .1371/journal.pone.0294231 Editor: Gilbert Sterling Octavius, Universitas Pelita Harapan, INDONESIA Received: January 31, 2023 Accepted: October 28, 2023 Published: November 16, 2023 Copyright: © 2023 Leonard et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: No datasets were generated or analysed during the current study. All relevant data from this study will be made available upon study completion. Funding: The support of the Technological University Dublin Scholarship Programme is gratefully acknowledged. The funders had and will not have a role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. STUDY PROTOCOL Supporting clinical decision making in the emergency department for paediatric patients using machine learning: A scoping review protocol Fiona Leonard1,2 *, Dympna O’Sullivan1, John Gilligan1, Nicola O’Shea3, Michael J. Barrett4,5 1 School of Computer Science, Technological University Dublin, Dublin, Ireland, 2 Digital Health Department, Children’s Health Ireland, Crumlin, Dublin, Ireland, 3 Library and Information Service, Children’s Health Ireland at Crumlin, Dublin, Ireland, 4 Department of Paediatric Emergency Medicine, Children’s Health Ireland at Crumlin, Dublin, Ireland, 5 Women’s and Children’s Health, School of Medicine, University College Dublin, Dublin, Ireland * [fiona.m.leonard@mytudublin.ie](fiona.m.leonard@mytudublin.ie) Abstract Introduction Machine learning as a clinical decision support system tool has the potential to assist clinicians who must make complex and accurate medical decisions in fast paced environments such as the emergency department. This paper presents a protocol for a scoping review, with the objective of summarising the existing research on machine learning clinical decision support system tools in the emergency department , focusing

FAQs

What is the purpose of the scoping review protocol in this document?

To summarise existing research on machine learning clinical decision support system tools in emergency departments, focusing on models appropriate for paediatric patients where a knowledge gap exists.

Which scoping review framework guides the study?

The protocol follows the scoping study framework of Arksey and O’Malley along with other guidelines.

What inclusion and exclusion criteria will be applied?

Included studies cover machine learning CDSS tools for any outcome and population (including paediatric/adult/mixed) used in emergency departments, from the last five years. Exclusions include grey literature such as letters, pre-prints, editorials, scoping/literature/narrative reviews, non-English full texts, protocols, surveys, and models based on synthesised data, as well as abstracts or unavailable full text.

Aug 4, 2026

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