Syndrome differentiation of fatty liver based on the whole network analysis theory

Yin ShouYi; Liu Tao; Wei HuaFeng; Ji Guang

Issue 5

May 2011

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Article Navigation > Journal of Clinical Hepatology > 2011 > 27(5): 474-478

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Syndrome differentiation of fatty liver based on the whole network analysis theory

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Published Date: 2011-05-20

Abstract

Abstract

Objective To investigate syndrome classification of fatty liver.Methods The relationship between syndrome differentiation and symptom of fatty liver was investigated by using SOM (Self-organizing feature map) neural network and whole network analysis method, and references for the standardization of syndrome differentiation were provided.Analysis on centrality was carried out to evaluate the importance of each symptom in each syndrome differentiation.Analysis on group centralization was performed to speculate the amount of the syndrome types and the accompanied degree of symptoms.Analysis on E-I index was carried out to speculate the reliability of the syndrome differentiation.Results The syndromes of fatty liver were found to be complex cluster syndromes rather than simple single syndrome.Conclusion Analysis of the relationship among different symptoms of fatty liver revealed a conspicuous Chinese medicine syndromes colonization concept.Standardization of syndrome differentiation of fatty liver is of great importance for its high reference value.The analysis method based on a complex cluster syndromes database was feasible.
- fatty liver,
- syndrome differ treatment,
- whole network analysis

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通讯作者: 陈斌, bchen63@163.com

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沈阳化工大学材料科学与工程学院沈阳 110142

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Syndrome differentiation of fatty liver based on the whole network analysis theory

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