TY - JOUR
T1 - Text Mining of Journal Articles for Sleep Disorder Terminologies
AU - Lam, Calvin
AU - Lai, Fu-Chih
AU - Wang, Chia Hui
AU - Lai, MH
AU - Hsu, N
AU - Chung, Min-Huey
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
KW - Journal Article
UR - http://www.ncbi.nlm.nih.gov/pubmed/27203858
UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85000352013&origin=resultslist&sort=plf-f&src=s&nlo=&nlr=&nls=&sid=d6c4b65b901e8e4d113257428ae20451&sot=a&sdt=a&sl=36&s=AU-ID%28%22Chung%2c+Min+Huey%22+22953113600%29&relpos=11&citeCnt=3&searchTerm=
UR - https://www.scopus.com/results/citedbyresults.uri?sort=plf-f&cite=2-s2.0-85000352013&src=s&imp=t&sid=81a051afb79247c432df9270342beb17&sot=cite&sdt=a&sl=0&origin=recordpage&editSaveSearch=&txGid=088a0982ad9c67e42e15877c988aa90d
U2 - 10.1371/journal.pone.0156031
DO - 10.1371/journal.pone.0156031
M3 - Article
C2 - 27203858
SN - 1932-6203
VL - 11
SP - e0156031
JO - PLoS One
JF - PLoS One
IS - 5
ER -