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整合型四象体质诊断模型的修正

Modification of the Integrated Sasang Constitutional Diagnostic Model.

作者信息

Nam Jiho, Jang Jun-Su, Kim Honggie, Kim Jong Yeol, Do Jun-Hyeong

机构信息

Medizen Humancare Inc., 20F Keungil Tower, 223 Teheran-ro, Seoul, Republic of Korea.

KM Fundamental Research Division, Korea Institute of Oriental Medicine, 1672 Yuseong-daero, Daejeon, Republic of Korea.

出版信息

Evid Based Complement Alternat Med. 2017;2017:9180159. doi: 10.1155/2017/9180159. Epub 2017 Nov 27.

Abstract

In 2012, the Korea Institute of Oriental Medicine proposed an objective and comprehensive physical diagnostic model to address quantification problems in the existing Sasang constitutional diagnostic method. However, certain issues have been raised regarding a revision of the proposed diagnostic model. In this paper, we propose various methodological approaches to address the problems of the previous diagnostic model. Firstly, more useful variables are selected in each component. Secondly, the least absolute shrinkage and selection operator is used to reduce multicollinearity without the modification of explanatory variables. Thirdly, proportions of SC types and age are considered to construct individual diagnostic models and classify the training set and the test set for reflecting the characteristics of the entire dataset. Finally, an integrated model is constructed with explanatory variables of individual diagnosis models. The proposed integrated diagnostic model significantly improves the sensitivities for both the male SY type (36.4% → 62.0%) and the female SE type (43.7% → 64.5%), which were areas of limitation of the previous integrated diagnostic model. The ideas of these new algorithms are expected to contribute not only to the scientific development of Sasang constitutional medicine in Korea but also to that of other diagnostic methods for traditional medicine.

摘要

2012年,韩国韩医学研究院提出了一种客观、全面的体质诊断模型,以解决现有四象体质诊断方法中的量化问题。然而,对于所提出的诊断模型的修订也出现了一些问题。在本文中,我们提出了各种方法来解决先前诊断模型存在的问题。首先,在每个组成部分中选择更有用的变量。其次,使用最小绝对收缩和选择算子来减少多重共线性,而无需修改解释变量。第三,考虑四象类型的比例和年龄来构建个体诊断模型,并对训练集和测试集进行分类,以反映整个数据集的特征。最后,用个体诊断模型的解释变量构建一个综合模型。所提出的综合诊断模型显著提高了男性少阳型(从36.4%提高到62.0%)和女性少阴型(从43.7%提高到64.5%)的敏感性,而这两个类型是先前综合诊断模型的局限性所在。这些新算法的理念不仅有望为韩国四象体质医学的科学发展做出贡献,也有望为其他传统医学诊断方法的发展做出贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7ae/5727843/05fa831ea014/ECAM2017-9180159.001.jpg

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