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1.
Chinese Journal of Information on Traditional Chinese Medicine ; (12): 17-21, 2017.
Article in Chinese | WPRIM | ID: wpr-511328

ABSTRACT

Objective To explore facial characteristics of patients with different organ diseases; To provide some references for objective study on TCM inspection information. Methods Smart TCM-I type Life Information Analysis Systems was used to detect facial characteristics of 510 patients with five zang-organs diseases. 36 specific quantitative parameters including red ?, green (G), blue (B) and hue (H), saturation (S), value (V) of the face, forehead, eyes, cheeks, nose and chin were collected, and the Kruskal M-Wallis H and Nemenyi test were used for statistical analysis. Results Among the 510 patients with five zang-organs diseases, 96 patients belonged to lung system diseases, 105 heart system diseases, 101 liver system diseases, 107 spleen and stomach system diseases and 101 kidney system diseases. There was statistical significance in R, G, B, H, S, and V in forehead, eyes, cheeks and nose. Conclusion Facial characteristics can provide objective references for the facial division of five zang-organs diseases.

2.
Chinese Journal of Information on Traditional Chinese Medicine ; (12): 124-128, 2015.
Article in Chinese | WPRIM | ID: wpr-465117

ABSTRACT

Standardization, objectification, and normalization of TCM syndromes are emphasis, difficulty, and hot issue of inheritance and development of TCM.With the technological development of computer and extensive application of multi-disciplinary integration, research methods for the identification of TCM syndrome classification emerge in endlessly. This article analyzed the application status of multivariate statistical analysis in the identification of TCM symdrome classification, summarized application status and existing problems of cluster analysis, PCA and factor analysis, discriminant analysis and Logistic regression analysis, and structure equation model in the identification of TCM symdrome classification, which provided references for further studies on identification methods of TCM symdrome classification.

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