A Review of Natural Language Processing in Medical Education

Natural language processing (NLP) aims to program machines to interpret human language as humans do. It could quantify aspects of medical education that were previously amenable only to qualitative methods. The application of NLP to medical education has been accelerating over the past several years...

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Detalles Bibliográficos
Autores principales: Chary, Michael, Parikh, Saumil, Manini, Alex F., Boyer, Edward W., Radeos, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Department of Emergency Medicine, University of California, Irvine School of Medicine 2019
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6324711/
https://www.ncbi.nlm.nih.gov/pubmed/30643605
http://dx.doi.org/10.5811/westjem.2018.11.39725
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author Chary, Michael
Parikh, Saumil
Manini, Alex F.
Boyer, Edward W.
Radeos, Michael
author_facet Chary, Michael
Parikh, Saumil
Manini, Alex F.
Boyer, Edward W.
Radeos, Michael
author_sort Chary, Michael
collection PubMed
description Natural language processing (NLP) aims to program machines to interpret human language as humans do. It could quantify aspects of medical education that were previously amenable only to qualitative methods. The application of NLP to medical education has been accelerating over the past several years. This article has three aims. First, we introduce the reader to NLP. Second, we discuss the potential of NLP to help integrate FOAM (Free Open Access Medical Education) resources with more traditional curricular elements. Finally, we present the results of a systematic review. We identified 30 articles indexed by PubMed as relating to medical education and NLP, 14 of which were of sufficient quality to include in this review. We close by discussing potential future work using NLP to advance the field of medical education in emergency medicine.
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spelling pubmed-63247112019-01-14 A Review of Natural Language Processing in Medical Education Chary, Michael Parikh, Saumil Manini, Alex F. Boyer, Edward W. Radeos, Michael West J Emerg Med Original Research Natural language processing (NLP) aims to program machines to interpret human language as humans do. It could quantify aspects of medical education that were previously amenable only to qualitative methods. The application of NLP to medical education has been accelerating over the past several years. This article has three aims. First, we introduce the reader to NLP. Second, we discuss the potential of NLP to help integrate FOAM (Free Open Access Medical Education) resources with more traditional curricular elements. Finally, we present the results of a systematic review. We identified 30 articles indexed by PubMed as relating to medical education and NLP, 14 of which were of sufficient quality to include in this review. We close by discussing potential future work using NLP to advance the field of medical education in emergency medicine. Department of Emergency Medicine, University of California, Irvine School of Medicine 2019-01 2018-12-12 /pmc/articles/PMC6324711/ /pubmed/30643605 http://dx.doi.org/10.5811/westjem.2018.11.39725 Text en Copyright: © 2019 Chary 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 Original Research
Chary, Michael
Parikh, Saumil
Manini, Alex F.
Boyer, Edward W.
Radeos, Michael
A Review of Natural Language Processing in Medical Education
title A Review of Natural Language Processing in Medical Education
title_full A Review of Natural Language Processing in Medical Education
title_fullStr A Review of Natural Language Processing in Medical Education
title_full_unstemmed A Review of Natural Language Processing in Medical Education
title_short A Review of Natural Language Processing in Medical Education
title_sort review of natural language processing in medical education
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6324711/
https://www.ncbi.nlm.nih.gov/pubmed/30643605
http://dx.doi.org/10.5811/westjem.2018.11.39725
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