Text Mining of Journal Articles for Sleep Disorder Terminologies

Calvin Lam, Fu-Chih Lai, Chia Hui Wang, MH Lai, N Hsu, Min-Huey Chung

研究成果: 雜誌貢獻文章同行評審

18 引文 斯高帕斯(Scopus)

摘要

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.
原文英語
頁(從 - 到)e0156031
期刊PLoS One
11
發行號5
DOIs
出版狀態已發佈 - 2016

指紋

深入研究「Text Mining of Journal Articles for Sleep Disorder Terminologies」主題。共同形成了獨特的指紋。

引用此