Research status and trend analysis of global biomedical text mining studies in recent 10 years

Xing Zhai, Zhihong Li, Kuo Gao, Youliang Huang, Lin Lin and Le Wang ()
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Xing Zhai: Beijing University of Chinese Medicine
Zhihong Li: Beijing University of Chinese Medicine
Kuo Gao: Beijing University of Chinese Medicine
Youliang Huang: Beijing University of Chinese Medicine
Lin Lin: HuBei University
Le Wang: Beijing University of Chinese Medicine

Scientometrics, 2015, vol. 105, issue 1, No 33, 509-523

Abstract: Abstract Objective In recent years, with the abrupt growth of the amount of biomedical literature, a lot of implicit laws and new knowledge were buried in the vast literature, while the text mining technology, if applied in the biomedical field, can integrate and analyze massive biomedical literature data, obtaining valuable information to improve people’s understanding of biomedical phenomena. This paper mainly discussed the research status of text mining technology applied in the biomedical field in recent 10 years in order to provide a reference for further studies of other researchers. Methods Biomedical text mining literature included in SCI from 2004 to 2013 were retrieved and filtered and then were analyzed from the perspectives of annual changes, regional distribution, research institutions, journals sources, research fields, keywords and so on. Results The total amount of global biomedical text mining literature is on the rise, among which literature relevant to named entity recognition, entity relation extraction, text categorization, text clustering, abbreviations extraction and co-occurrence analysis take up a large percentage; studies in USA and the UK are in the leading position. Conclusion Compared with other much more mature research topics, the application of text mining technology in biomedicine is still a relatively new research field worldwide, while with the constantly improving awareness of this field and deepening researches in this area, a number of core research areas, core research institutes and core research fields have been formed in this field. Therefore, further researches of this field will inject new vitality in the development of biomedicine.

Keywords: Text mining; Biomedical; Development trends; Bibliometrics; SCI (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s11192-015-1700-9

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