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KMID : 1150720180070030231
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Integrative Medicine Research
2018 Volume.7 No. 3 p.231 ~ p.237
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Trends in deqi research: a text mining and network analysis
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Kwon O-Sang
Kim Jun-Beom
Choi Kwang-Ho
Ryu Yeon-Hee
Park Ji-Eun
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Abstract
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Background: Deqi is a term describing a special state of the human body, which is ready to cure itself through acupuncture stimulation and is believed to be a key factor in acupuncture treatment. However, knowledge about deqi remains subjective. Therefore, in this study, we aimed to determine the factors related to deqi generation based on present studies to promote the progression of deqi research.
Methods: A term frequency?inverse document frequency (Tf-idf) was used to extract key elements from the abstracts of 148 articles searched from Pubmed, and the network structure between key elements was analyzed.
Results: A total of 37 items were extracted from the abstracts. Each item was categorized into one of three groups (acupuncture-related sensation, interventions or organ/mechanism). Acupuncture-related sensation was studied by comparing the items in the interventions group with the organ/mechanism group. Key elements related to deqi generation included muscles from the organ/mechanism group and intensity, depth and pressure from the interventions group. Items that belonged to the acupuncture-related sensation group were divided into two clusters: one cluster consisted of pain, tingling, aching, soreness, heaviness, fullness and numbness; the other included warm, cold and dull.
Conclusion: We could find out that the trend of deqi was leaning towards the interventions group, which related to the generation of deqi; thus, authors concluded that the mechanism studies, which are aimed to investigate why deqi is generated or what kind of meanings it has, are needed for evolution of acupuncture theory and application of the brand new technologies and related devices.
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KEYWORD
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Deqi, Text mining, Network analysis, Acupuncture, Trend
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