Cargando…

Applications of Machine Learning Approaches in Emergency Medicine; a Review Article

Using artificial intelligence and machine learning techniques in different medical fields, especially emergency medicine is rapidly growing. In this paper, studies conducted in the recent years on using artificial intelligence in emergency medicine have been collected and assessed. These studies bel...

Descripción completa

Detalles Bibliográficos
Autores principales: Shafaf, Negin, Malek, Hamed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Shahid Beheshti University of Medical Sciences 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6732202/
https://www.ncbi.nlm.nih.gov/pubmed/31555764
_version_ 1783449784831442944
author Shafaf, Negin
Malek, Hamed
author_facet Shafaf, Negin
Malek, Hamed
author_sort Shafaf, Negin
collection PubMed
description Using artificial intelligence and machine learning techniques in different medical fields, especially emergency medicine is rapidly growing. In this paper, studies conducted in the recent years on using artificial intelligence in emergency medicine have been collected and assessed. These studies belonged to three categories: prediction and detection of disease; prediction of need for admission, discharge and also mortality; and machine learning based triage systems. In each of these categories, the most important studies have been chosen and accuracy and results of the algorithms have been briefly evaluated by mentioning machine learning techniques and used datasets.
format Online
Article
Text
id pubmed-6732202
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Shahid Beheshti University of Medical Sciences
record_format MEDLINE/PubMed
spelling pubmed-67322022019-09-25 Applications of Machine Learning Approaches in Emergency Medicine; a Review Article Shafaf, Negin Malek, Hamed Arch Acad Emerg Med Review Article Using artificial intelligence and machine learning techniques in different medical fields, especially emergency medicine is rapidly growing. In this paper, studies conducted in the recent years on using artificial intelligence in emergency medicine have been collected and assessed. These studies belonged to three categories: prediction and detection of disease; prediction of need for admission, discharge and also mortality; and machine learning based triage systems. In each of these categories, the most important studies have been chosen and accuracy and results of the algorithms have been briefly evaluated by mentioning machine learning techniques and used datasets. Shahid Beheshti University of Medical Sciences 2019-06-03 /pmc/articles/PMC6732202/ /pubmed/31555764 Text en This is an Open Access article distributed under the terms of the Creative Commons Attribution License, (http://creativecommons.org/licenses/by/3.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review Article
Shafaf, Negin
Malek, Hamed
Applications of Machine Learning Approaches in Emergency Medicine; a Review Article
title Applications of Machine Learning Approaches in Emergency Medicine; a Review Article
title_full Applications of Machine Learning Approaches in Emergency Medicine; a Review Article
title_fullStr Applications of Machine Learning Approaches in Emergency Medicine; a Review Article
title_full_unstemmed Applications of Machine Learning Approaches in Emergency Medicine; a Review Article
title_short Applications of Machine Learning Approaches in Emergency Medicine; a Review Article
title_sort applications of machine learning approaches in emergency medicine; a review article
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6732202/
https://www.ncbi.nlm.nih.gov/pubmed/31555764
work_keys_str_mv AT shafafnegin applicationsofmachinelearningapproachesinemergencymedicineareviewarticle
AT malekhamed applicationsofmachinelearningapproachesinemergencymedicineareviewarticle