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KMID : 1123920180320030149
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Korean Journal of Oriental Physiology and Pathology
2018 Volume.32 No. 3 p.149 ~ p.156
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Identifying Theoretical Characteristics of Traditional Medicines in Korea, China, and Japan through the Herb Usage Data
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Park Mu-Sun
Lee Choong-Yeol
Lee Tae-Hee
Kim Youn-Sub
Kim Chang-Eop
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Abstract
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Traditional medicines (TM) in Korea, China, and Japan share most of the theories and therapeutic tools, but there are also differences due to their unique histories and cultures. Here, we aim to identify the differences in the utilization of TM theory between three countries by analyzing herb usage data in terms of the related traditional theories. Herb usage data of each country was collected from "Investigation of Korean medicine use and herbal medicine consumption survey" (Korea), "Analytical report on circulation of key Chinese medicinal materials" (China), and "Survey report on raw material crude drug usage" (Japan). Fifty five herbs with sixty features belonging to five theoretical categories (four properties, five tastes, targeting meridians, treatment strategies, and herbal parts) were selected and analyzed. Weight Sum Model (WSM) and Network-Based Group Features (NBGF) were used to compare the theoretical characteristics of TM between three countries. For the statistical evaluation, we developed and applied Herb Set Enrichment Analysis (HSEA) for WSM and NBGF results. HSEA for WSM results revealed the kidney meridian were targeted more in Korea than Japan, while the spleen meridian were targeted more in Japan than Korea. Herbs with sour taste were used more in Japan than China. HSEA for NBGF results found that NBGF including warm, neutral, sweet, and tonifying features were more dominant in Korea and than Japan, while NBGF including cold, bitter, heat-clearing features were more dominant in Japan than the others. These results suggest that TM in Korea, China, and Japan have unique aspects of practice patterns and theoretical utilization.
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KEYWORD
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Traditional medicine, Herb usage, Theoretical utilization, Data-driven
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