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Machine Learning in Relation to Emergency Medicine Clinical and Operational Scenarios: An Overview

Health informatics is a vital technology that holds great promise in the healthcare setting. We describe two prominent health informatics tools relevant to emergency care, as well as the historical background and the current state of informatics. We also identify recent research findings and practic...

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Autores principales: Lee, Sangil, Mohr, Nicholas M., Street, W. Nicholas, Nadkarni, Prakash
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Department of Emergency Medicine, University of California, Irvine School of Medicine 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6404711/
https://www.ncbi.nlm.nih.gov/pubmed/30881539
http://dx.doi.org/10.5811/westjem.2019.1.41244
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author Lee, Sangil
Mohr, Nicholas M.
Street, W. Nicholas
Nadkarni, Prakash
author_facet Lee, Sangil
Mohr, Nicholas M.
Street, W. Nicholas
Nadkarni, Prakash
author_sort Lee, Sangil
collection PubMed
description Health informatics is a vital technology that holds great promise in the healthcare setting. We describe two prominent health informatics tools relevant to emergency care, as well as the historical background and the current state of informatics. We also identify recent research findings and practice changes. The recent advances in machine learning and natural language processing (NLP) are a prominent development in health informatics overall and relevant in emergency medicine (EM). A basic comprehension of machine-learning algorithms is the key to understand the recent usage of artificial intelligence in healthcare. We are using NLP more in clinical use for documentation. NLP has started to be used in research to identify clinically important diseases and conditions. Health informatics has the potential to benefit both healthcare providers and patients. We cover two powerful tools from health informatics for EM clinicians and researchers by describing the previous successes and challenges and conclude with their implications to emergency care.
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spelling pubmed-64047112019-03-15 Machine Learning in Relation to Emergency Medicine Clinical and Operational Scenarios: An Overview Lee, Sangil Mohr, Nicholas M. Street, W. Nicholas Nadkarni, Prakash West J Emerg Med Emergency Department Operations Health informatics is a vital technology that holds great promise in the healthcare setting. We describe two prominent health informatics tools relevant to emergency care, as well as the historical background and the current state of informatics. We also identify recent research findings and practice changes. The recent advances in machine learning and natural language processing (NLP) are a prominent development in health informatics overall and relevant in emergency medicine (EM). A basic comprehension of machine-learning algorithms is the key to understand the recent usage of artificial intelligence in healthcare. We are using NLP more in clinical use for documentation. NLP has started to be used in research to identify clinically important diseases and conditions. Health informatics has the potential to benefit both healthcare providers and patients. We cover two powerful tools from health informatics for EM clinicians and researchers by describing the previous successes and challenges and conclude with their implications to emergency care. Department of Emergency Medicine, University of California, Irvine School of Medicine 2019-03 2019-02-14 /pmc/articles/PMC6404711/ /pubmed/30881539 http://dx.doi.org/10.5811/westjem.2019.1.41244 Text en Copyright: © 2019 Lee et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) License. See: http://creativecommons.org/licenses/by/4.0/
spellingShingle Emergency Department Operations
Lee, Sangil
Mohr, Nicholas M.
Street, W. Nicholas
Nadkarni, Prakash
Machine Learning in Relation to Emergency Medicine Clinical and Operational Scenarios: An Overview
title Machine Learning in Relation to Emergency Medicine Clinical and Operational Scenarios: An Overview
title_full Machine Learning in Relation to Emergency Medicine Clinical and Operational Scenarios: An Overview
title_fullStr Machine Learning in Relation to Emergency Medicine Clinical and Operational Scenarios: An Overview
title_full_unstemmed Machine Learning in Relation to Emergency Medicine Clinical and Operational Scenarios: An Overview
title_short Machine Learning in Relation to Emergency Medicine Clinical and Operational Scenarios: An Overview
title_sort machine learning in relation to emergency medicine clinical and operational scenarios: an overview
topic Emergency Department Operations
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6404711/
https://www.ncbi.nlm.nih.gov/pubmed/30881539
http://dx.doi.org/10.5811/westjem.2019.1.41244
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