A Classical Acupuncture Text from
Korea
Throughout the history of East Asian
medicine, different kinds of acupuncture treatment experiences have been
accumulated in classical medical texts. Reexamining knowledge from classical
medical texts is expected to provide meaningful information that could be
utilized in current medical practices. In this study, we used data mining
methods to analyze the association between acupoints and patterns of disorder
with the classical medical book DongUiBoGam of Korean medicine. Using the term
frequency-inverse document frequency (tf-idf) method, we quantified the
significance of acupoints to its targeting patterns and, conversely, the
significance of patterns to acupoints. Through these processes, we extracted
characteristics of each acupoint based on its treating patterns. We also drew
practical information for selecting acupoints on certain patterns according to
their association. Data analysis on DongUiBoGam’s acupuncture treatment gave us
an insight into the main idea of DongUiBoGam. We strongly believe that our
approach can provide a novel understanding of unknown characteristics of
acupoint and pattern identification from the classical medical text using data
mining methods.
Source:
Taehyung Lee, Won-Mo Jung, In-Seon Lee, Ye-Seul Lee, Hyejung Lee, Hi-Joon Park, Namil Kim, and
Younbyoung Chae. Data Mining of Acupoint Characteristics from the Classical
Medical Text: DongUiBoGam of Korean Medicine. Evidence-Based Complementary and
Alternative Medicine. Volume 2014 (2014), Article ID 329563.
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