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Text Mining of Journal Articles for Sleep Disorder Terminologies
OBJECTIVE: Research on publication trends in journal articles on sleep disorders (SDs) and the associated methodologies by using text mining has been limited. The present study involved text mining for terms to determine the publication trends in sleep-related journal articles published during 2000–...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4874549/ https://www.ncbi.nlm.nih.gov/pubmed/27203858 http://dx.doi.org/10.1371/journal.pone.0156031 |
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author | Lam, Calvin Lai, Fu-Chih Wang, Chia-Hui Lai, Mei-Hsin Hsu, Nanly Chung, Min-Huey |
author_facet | Lam, Calvin Lai, Fu-Chih Wang, Chia-Hui Lai, Mei-Hsin Hsu, Nanly Chung, Min-Huey |
author_sort | Lam, Calvin |
collection | PubMed |
description | OBJECTIVE: Research on publication trends in journal articles on sleep disorders (SDs) and the associated methodologies by using text mining has been limited. The present study involved text mining for terms to determine the publication trends in sleep-related journal articles published during 2000–2013 and to identify associations between SD and methodology terms as well as conducting statistical analyses of the text mining findings. METHODS: SD and methodology terms were extracted from 3,720 sleep-related journal articles in the PubMed database by using MetaMap. The extracted data set was analyzed using hierarchical cluster analyses and adjusted logistic regression models to investigate publication trends and associations between SD and methodology terms. RESULTS: MetaMap had a text mining precision, recall, and false positive rate of 0.70, 0.77, and 11.51%, respectively. The most common SD term was breathing-related sleep disorder, whereas narcolepsy was the least common. Cluster analyses showed similar methodology clusters for each SD term, except narcolepsy. The logistic regression models showed an increasing prevalence of insomnia, parasomnia, and other sleep disorders but a decreasing prevalence of breathing-related sleep disorder during 2000–2013. Different SD terms were positively associated with different methodology terms regarding research design terms, measure terms, and analysis terms. CONCLUSION: Insomnia-, parasomnia-, and other sleep disorder-related articles showed an increasing publication trend, whereas those related to breathing-related sleep disorder showed a decreasing trend. Furthermore, experimental studies more commonly focused on hypersomnia and other SDs and less commonly on insomnia, breathing-related sleep disorder, narcolepsy, and parasomnia. Thus, text mining may facilitate the exploration of the publication trends in SDs and the associated methodologies. |
format | Online Article Text |
id | pubmed-4874549 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-48745492016-06-09 Text Mining of Journal Articles for Sleep Disorder Terminologies Lam, Calvin Lai, Fu-Chih Wang, Chia-Hui Lai, Mei-Hsin Hsu, Nanly Chung, Min-Huey PLoS One Research Article OBJECTIVE: Research on publication trends in journal articles on sleep disorders (SDs) and the associated methodologies by using text mining has been limited. The present study involved text mining for terms to determine the publication trends in sleep-related journal articles published during 2000–2013 and to identify associations between SD and methodology terms as well as conducting statistical analyses of the text mining findings. METHODS: SD and methodology terms were extracted from 3,720 sleep-related journal articles in the PubMed database by using MetaMap. The extracted data set was analyzed using hierarchical cluster analyses and adjusted logistic regression models to investigate publication trends and associations between SD and methodology terms. RESULTS: MetaMap had a text mining precision, recall, and false positive rate of 0.70, 0.77, and 11.51%, respectively. The most common SD term was breathing-related sleep disorder, whereas narcolepsy was the least common. Cluster analyses showed similar methodology clusters for each SD term, except narcolepsy. The logistic regression models showed an increasing prevalence of insomnia, parasomnia, and other sleep disorders but a decreasing prevalence of breathing-related sleep disorder during 2000–2013. Different SD terms were positively associated with different methodology terms regarding research design terms, measure terms, and analysis terms. CONCLUSION: Insomnia-, parasomnia-, and other sleep disorder-related articles showed an increasing publication trend, whereas those related to breathing-related sleep disorder showed a decreasing trend. Furthermore, experimental studies more commonly focused on hypersomnia and other SDs and less commonly on insomnia, breathing-related sleep disorder, narcolepsy, and parasomnia. Thus, text mining may facilitate the exploration of the publication trends in SDs and the associated methodologies. Public Library of Science 2016-05-20 /pmc/articles/PMC4874549/ /pubmed/27203858 http://dx.doi.org/10.1371/journal.pone.0156031 Text en © 2016 Lam et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Lam, Calvin Lai, Fu-Chih Wang, Chia-Hui Lai, Mei-Hsin Hsu, Nanly Chung, Min-Huey Text Mining of Journal Articles for Sleep Disorder Terminologies |
title | Text Mining of Journal Articles for Sleep Disorder Terminologies |
title_full | Text Mining of Journal Articles for Sleep Disorder Terminologies |
title_fullStr | Text Mining of Journal Articles for Sleep Disorder Terminologies |
title_full_unstemmed | Text Mining of Journal Articles for Sleep Disorder Terminologies |
title_short | Text Mining of Journal Articles for Sleep Disorder Terminologies |
title_sort | text mining of journal articles for sleep disorder terminologies |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4874549/ https://www.ncbi.nlm.nih.gov/pubmed/27203858 http://dx.doi.org/10.1371/journal.pone.0156031 |
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