PDF下载 ( 4053 KB)
Syndrome differentiation of fatty liver based on the whole network analysis theory
-
摘要: 目的探讨脂肪肝中医证候的分类。方法运用整体网分析方法对SOM神经网络整理出的关系数据集进行整体网络结构分析,为脂肪肝的中医辨证提供参考依据。主要考量中心性用以评价各个症状在"辨证论治"中的重要程度;考量中心势用以推测论证型的多寡和兼杂程度;考量分派指数用以推测理想辨证的可靠程度。结果脂肪肝疾病的中医辨证,较难得到单一的主证,辨证体系比较复杂,证型较多;脂肪肝辨证中较易出现兼杂证。结论基于症状与症状的关联进行分析可以发现中医证候的集群现象;提出脂肪肝的中医辨证标准具有较高参考价值;基于兼杂证型的调查研究数据,提取中医基本证候类型的思路是可行的。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.
-
Key words:
- fatty liver /
- syndrome differ treatment /
- whole network analysis
-
[1]Wilkinson DM, Huberman BA.A method forfinding communities of related genes[J].Proc Natl Acad Sci U S A, 2004, 101 (Suppl 1) :5241-5248. [2]Holme P, Huss M, Jeong H.Subnetwork hierarchies of biochemical pathways[J].Bioinformatics, 2003, 19 (4) :532-538. [3]Sakata S, Yamamori T.Topological relationships between brain and social networks[J].Neural Networks, 2007, 20 (1) :12-21. [4]Bodin?, Crona B, Ernstson H.Social networks in natural resource management:what is there to learn from a structural perspective[J].Ecology and Society, 2006, 11 (2) :r2. [5]Palla G, Derényi I, Farkas I, et al.Uncovering the overlapping community structure of complex networks in nature and society[J].Nature, 2005, 435 (7043) :814-818. [6]中华肝脏病学会脂肪肝和酒精性肝病学组.非酒精性脂肪肝诊断标准[J].肝脏, 2002, 7 (4) :附页2. [7]刘军.整体网分析讲义[M].上海:格致出版社, 2009:97-103. [8]罗家德.社会网分析讲义 (第二版) [M].北京:社会科学文献出版社, 2010:188-189, 191-194. [9]Clauset A, Newman ME, Moore C.Finding community structure in very large networks[J].Phys Rev E Stat Nonlin Soft Matter Phys, 2004, 70 (6 Pt 2) :066111. [10]Newman ME, Girvan M.Finding and evaluating community structure in networks[J].Phys Rev E Stat Nonlin Soft Matter Phys, 2004, 69 (2 Pt 2) :026113. [11]Girvan M, Newman ME.Community structure in social and biological networks[J].Proc Natl Acad Sci U S A, 2002, 99 (12) :7821-7826. -
本文二维码
计量
- 文章访问数: 2872
- HTML全文浏览量: 8
- PDF下载量: 877
- 被引次数: 0
下载:
