Research on Clinical Diagnostic Models of IPF Syndromes in TCM Based on Dynamic Kohonen Network and Decision Tree

Author

Jinliang, Hu ; Caiqing, Yue ; Jiansheng, Li ; Jianjing, Shen

Author_Institution

Coll. of Inf. Eng., First Affiliated Hosp., Henan Univ. of Traditional Chinese Medicine, Zhengzhou, China

Volume

2

fYear

2010

fDate

16-17 Dec. 2010

Firstpage

107

Lastpage

110

Abstract

To explore methods of establishing Clinical Diagnostic models of Idiopathic pulmonary fibrosis(IPF) syndromes in TCM (traditional Chinese medicine) by studying the results of data mining of IPF. The end fuzzy rule and result were get by the contrast of dynamic kohonen network and Decision Tree, their reliability was tested with the Fisher-iris data. The coincident diagnostic rate of dynamic kohonen network and Decision Tree reached 94% and 92% in comparison of the test data. The model, for its rational characteristics, can be applied to the study of diagnostic criterion for IPF syndromes.

Keywords

decision trees; medical diagnostic computing; self-organising feature maps; IPF syndromes; TCM; clinical diagnostic models; data mining; decision tree; dynamic Kohonen network; idiopathic pulmonary fibrosis; traditional Chinese medicine; Artificial neural networks; Data mining; Diseases; Lungs; Medical diagnostic imaging; Neurons; Decision Tree; IPF; data mining; dynamic kohonen network;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems (GCIS), 2010 Second WRI Global Congress on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-9247-3

Type

conf

DOI

10.1109/GCIS.2010.204

Filename

5708798