발간년도 : [2022]
| 논문정보 |
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| 논문명(한글) |
[Vol.17, No.5] An Analysis of the Research Trends of Five Traditional Korean Medicine Prescriptions Using Text Mining: Leveraging PubMed Articles |
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| 논문투고자 |
Sang-Jun Yea, Sang-Hyun Kim |
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| 논문내용 |
In order to analyze and examine research trends on traditional Korean medicine (TKM) prescriptions, we analyzed the publication year and study type of the collected papers on TKM prescriptions. In addition, we carried out the text mining on the diseases related to the TKM prescriptions from abstract in PubMed. Then we identified the research trends of top five TKM prescriptions and discussed the TKM indications and the direction of modern biomedical researches. On the basis of the number of papers queried in PubMed, the top five TKM prescriptions, sosiho-tang, hwanglyeonhaedok-tang, bojungikgi-tang, socheongryong-tang, and gamisoyo-san were selected for successive analysis. According to the annual analysis, the number of papers on the identified prescription started from the beginning of 1980 and continued to increase. According to the analysis results by study type, in-vivo studies were found to be the mainstream in studies on the prescription of the 4 TKM prescriptions except gamisoyo-san. In addition, on average, there were three to four disease names per abstract, and then we mapped recognized diseases to the diseases category of the MeSH Tree. Through the comparative analysis between traditional medical treatment concepts and modern scientific disease categories, it was confirmed that they tried to study the material of TKM prescriptions in an appropriate biomedical fields. Although the concept of TKM diagnosis and treatment is difficult to categorize, due to these characteristics, TKM prescriptions are being applied to various disease studies. |
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