Data Mining of Acupoint Characteristics from the Classical Medical Text:DongUiBoGamof Korean Medicine

Abstract

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.

Understanding Mind-Body Interaction from the Perspective of East Asian Medicine

“…This text serves as the fundamental doctrinal source of medical classics such as the Huangdi Neijing and ShangHan Lun as well as more recent medical texts, including the Wanbinghuichun (1587) from China and the HyangYakJipSeongBang (1443) and EuiRimChwalYo (1567) from Korea. In fact, the DongUiBoGam was written as the summation of East Asian medicine knowledge up to the year of its compilation and served as the core text for medical theories and perspectives as understood in Korean medicine [22]. …”

“…The picture of ShinHyungJangBuDo on the first page of the DongUiBoGam illustrates this concept by emphasizing the body organs, or viscera, and the major pathway through which the qi passes by breathing [22]. Thus, in the DongUiBoGam , emotions are categorized into seven different groups: anger, happiness, thoughtfulness, sadness, anxiety, fear, and surprise.…”

Characterization of Five Shu Acupoint Pattern in Saam Acupuncture Using Text Mininig

“…한의학의 경혈 및 침구 분야 연구는 주로 자침 행위를 통한 치료 가 어떤 의생명과학 메카니즘을 통해 이루어지는지를 밝히는 쪽에 집중이 되어 왔다 1,2) . 병증에 따른 경혈의 선혈 원리는 한의학 고전 문헌이나 임상에서 가장 중요시 되는 요소 중 하나이지만, 상대적 으로 이와 관련된 연구는 많이 이루어지지 못하였다 3,4) .…”

Implementation of TF-IDF Algorithm to detect Human Eye Factors Affecting the Health Service System

“…Some studies use text mining to obtain comparisons of original data with modified data or similar data [8] [9]. Other reviews of text mining use the term frequency-inverse document frequency (TF-IDF) algorithm to provide analysis related to acupoint characteristics and identification of unknown patterns from classical medical texts [10]. The TF-IDF method can also provide data classification results as in other data mining methods such as the c.45 algorithm [11], as in research conducted by Herwijayanti regarding online news classification [12].…”