[논문]데이터 마이닝을 이용한 한의비만변증 설문지 재평가: 실제 임상에서 수집한 설문응답 기반으로

오지홍; 왕징화; 최선미; 김호준

doi:10.15429/jkomor.2021.21.2.80

[국내논문] 데이터 마이닝을 이용한 한의비만변증 설문지 재평가: 실제 임상에서 수집한 설문응답 기반으로
Re-evaluation of Obesity Syndrome Differentiation Questionnaire Based on Real-world Survey Data Using Data Mining 원문보기

한방비만학회지 = Journal of Korean Medicine for Obesity Research, v.21 no.2, 2021년, pp.80 - 94

오지홍 (동국대학교 한의과대학 한방재활의학교실) , 왕징화 (대전대학교 동서생명과학연구원) , 최선미 (한국한의학연구원 한의약데이터부) , 김호준 (동국대학교 한의과대학 한방재활의학교실)

Abstract ▼ AI-Helper

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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표/그림 (11)

표 Table 1. Obesity Syndrome Differentiation Questionnaire
그림 Fig. 1. Flow chart of study.
표 Table 1. Continued
그림 Fig. 2. Histogram of frequency distribution of obesity syndrome differentiation. The x-axis shows obesity syndrome differentiation and the y-axis is the frequency. The legend in the upper right corner describes the gender with the number. FR: food retention, YD: yang deficiency, LS: liver qi stagnation, PH: phlegm, BS: blood stasis, SD: spleen deficiency.
그림 Fig. 3. Boxplot of BMI by obesity syndrome. The central line in each box indicates the median, lower and upper limits of the box indicate 25th and 75th percentiles, and whiskers indicate minimum and maximum of observed values. BMI: body mass index, FR: food retention, YD: yang deficiency, LS: liver qi stagnation, PH: phlegm, BS: blood stasis, SD: spleen deficiency. The difference between subjects by obesity syndrome differentiation were significant in Kruskal Wallis test (P=0.03). ** refers significant difference between two groups after using Dunn post hoc test (P=0.015, with adjusted P-value using Bonferroni).
표 Table 2. Variance of Questions and Feature Selection by Variance Threshold
표 Table 3. Statistical Characteristics of Excluded Variables
그림 Fig. 4. K-means clustering of 39 selected questions after principal component analysis (PCA). The first two principal components were plotted and the number of clusters was set to K=3. Each data point indicates the question of obesity syndrome questionnaire. The red x indicates the centroid of the cluster. Different colors of datapoints are labeled according to their clusters by K-means clustering; green circle (Cluster 1); orange circle (Cluster 2); blue circle (Cluster 3). Different shapes of datapoints are labeled according to the syndrome to which the questions contribute. FR: food retention, YD: yang deficiency, LS: liver qi stagnation, PH: phlegm, BS: blood stasis, SD: spleen deficiency.
그림 Fig. 5. Heatmap with dendrogram of 39 selected questions based on the Euclidean distance. The y-axis represents 39 selected questions and x-axis represents each subject. The colors in the heatmap represent answers range from 1 to 5 (shown in color bar). The circles in the x-axis indicate different clusters resulted from K-means clustering; GREen circle (Cluster 1); orange circle (Cluster 2); blue circle (Cluster 3).
그림 Fig. 6. Stacked Histogram of distribution of responses by obesity syndrome differentiation. X-axis was arranged in question cluster order and red vertical lines represent the cluster divider. Y-axis indicates frequency of responses according to the score and each score is marked with different colors. FR: food retention, LS: liver qi stagnation, YD: yang deficiency, PH: phlegm, SD: spleen deficiency, BS: blood stasis.
그림 Fig. 7. PCA and PCA biplot of subjects (a) The first two principal components were plotted. Each data point indicates subject. Different colors of datapoints are labeled according to their obesity syndrome differentiation; Orange circle (FR); sky blue circle (LS); grey circle (other obesity syndromes except FR, LS). (b) PCA biplot of the subjects showing the loading of 20 questions which mainly affect the distribution (arrows). The length of arrows approximates the variance of the questions, whereas the angles between the questions approximate their correlations. Closed data points have similar scores on the PCA components. PCA: principal component analysis, FR: food retention syndrome, LS: liver qi stagnation syndrome.

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상세보기
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