Grey correlation analysis on influencing factors of Yang deficiency constitution

Q3 Medicine Digital Chinese Medicine Pub Date : 2023-06-01 DOI:10.1016/j.dcmed.2023.07.005
Luo Yue , Jiang Luxia , Yang Shengwen , Su Biliang , Ou Jintao , Wen Chuanbiao
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Abstract

Objective

To explore the influencing factors of Yang deficiency constitution in traditional Chinese medicine (TCM) from the perspective of mathematics with the use of calculation formulas, so as to protect patients from getting diseases caused by Yang deficiency constitution and provide suggestions for TCM disease prevention.

Methods

Based on the classification and determination criteria of TCM constitution implemented by China Association of Chinese Medicine, data for 24 solar terms from May 5, 2020 (Start of Summer) to April 20, 2021 (Grain Rain) for the identification of Yang deficiency were collected by mobile constitution identification system. The grey correlation analysis method was used to determine the grey correlation degree of the factors influencing Yang deficiency constitution. In addition, a random forest model was constructed for the verification of the results from the grey correlation analysis, and for the evaluation of correlation degree between Yang deficiency constitution and its influencing factors.

Results

A total of 16 259 sets of data were collected from healthy or sub-healthy individuals aged from 18 to 60 years living in the central and northeastern parts of Sichuan Province (China) for the identification of TCM constitutions. After screening and preprocessing, a total of 544 sets of data for the identification of Yang deficiency constitution, involving 18 aspects of factors influencing Yang deficiency constitution. The results of the grey correlation analysis showed that there were 12 influencing factors whose grey correlation degree with Yang deficiency constitution was greater than 0.6. The accuracy of these 12 influencing factors with the training set and validation set of the Yang deficiency constitution random forest model were 98.39% and 93.12%, respectively.

Conclusion

In the sample data selected in this paper, grey correlation analysis is the appropriate technology to analyze the influencing factors of Yang deficiency constitution. It provides a new idea and a new methodological reference for the research and analysis of the influencing factors of TCM constitution.

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阳虚体质影响因素的灰色关联分析
目的运用数学计算公式,探讨中医阳虚体质的影响因素,保护患者不患阳虚体质引起的疾病,为中医疾病预防提供建议。方法根据中国中医药学会实施的中医体质分类判定标准,采用移动体质鉴定系统采集2020年5月5日(立夏)至2021年4月20日(谷雨)24个节气的阳虚证候数据。采用灰色关联分析方法,确定影响阳虚体质因素的灰色关联度。此外,还构建了一个随机森林模型,以验证灰色关联分析的结果,并评估阳虚体质与其影响因素之间的相关性。结果收集川中、川东北地区18~60岁健康或亚健康人群的16259组中医体质鉴定资料。经过筛选和预处理,共有544组数据用于阳虚体质的鉴定,涉及阳虚体质影响因素的18个方面。灰色关联分析结果表明,有12个影响因素与阳虚体质的灰色关联度大于0.6。这12个影响因素与阳虚体质随机森林模型的训练集和验证集的准确率分别为98.39%和93.12%。结论在本文选取的样本数据中,灰色关联分析是分析阳虚体质影响因素的合适技术。为中医体质影响因素的研究和分析提供了新的思路和方法参考。
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来源期刊
Digital Chinese Medicine
Digital Chinese Medicine Medicine-Complementary and Alternative Medicine
CiteScore
1.80
自引率
0.00%
发文量
126
审稿时长
63 days
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