데이터 마이닝을 이용한 한의비만변증 설문지 재평가

• 영문명: Re-evaluation of Obesity Syndrome Differentiation Questionnaire Based on Real-world Survey Data Using Data Mining
• 발행기관: 한방비만학회
• 저자명: 오지홍(Jihong Oh) 왕징화(Jing-Hua Wang) 최선미(Sun-Mi Choi) 김호준(Hojun Kim)
• 간행물 정보: 『대한한방비만학회지』제21권 2호, 80~94쪽, 전체 15쪽
• 주제분류: 의약학 > 한의학
• 파일형태: PDF
• 발행일자: 2021.12.31

영문 초록

Objectives: The purpose of this study is to re-evaluate the importance of questions of obesity syndrome differentiation (OSD) questionnaire based on real-world survey and to explore the possibility of simplifying OSD types. Methods: The OSD frequency was identified, and variance threshold feature selection was performed to filter the questions. Filtered questions were clustered by K-means clustering and hierarchical clustering. After principal component analysis (PCA), the distribution patterns of the subjects were identified and the differences in the syndrome distribution were compared. Results: The frequency of OSD in spleen deficiency, phlegm (PH), and blood stasis (BS) was lower than in food retention (FR), liver qi stagnation (LS), and yang deficiency. We excluded 13 questions with low variance, 7 of which were related to BS. Filtered questions were clustered into 3 groups by K-means clustering; Cluster 1 (17 questions) mainly related to PH, BS syndromes; Cluster 2 (11 questions) related to swelling, and indigestion; Cluster 3 (11 questions) related to overeating or emotional symptoms. After PCA, significant different patterns of subjects were observed in the FR, LS, and other obesity syndromes. The questions that mainly affect the FR distribution were digestive symptoms. And emotional symptoms mainly affect the distribution of LS subjects. And other obesity syndrome was partially affected by both digestive and emotional symptoms, and also affected by symptoms related to poor circulation. Conclusions: In-depth data mining analysis identified relatively low importance questions and the potential to simplify OSD types.

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키워드

Syndrome differentiation Syndrome differentiation questionnaire pattern identification Korean traditional medicine Data mining Principal component analysis