DocumentCode :
3197787
Title :
An intelligent diagnosis method for Chronis hepatitis B in TCM
Author :
Na Chu ; Min Zhou ; Yu Zhao ; Zhiying Che ; Lizhuang Ma
Author_Institution :
Dept. of Comput. Sci. & Technol., Dalian Neusoft Inst. of Inf., Dalian, China
fYear :
2013
fDate :
18-21 Dec. 2013
Firstpage :
20
Lastpage :
22
Abstract :
In traditional Chinese medicine (TCM), it is frequently found that more than one syndrome of a patient are recognized in clinical practice, which has its own symptoms and signs. While, most algorithms are used to solve issues of syndrome diagnosis that only focus on one syndrome. Therefore, we proposed a hybrid intelligent syndrome diagnosis (HISD) model. Methods. The HTSD model combined feature selection methods to select the significant symptoms and signs corresponding to syndromes of CHB, and combined probability-classification methods to obtain the main syndrome and accompanying syndromes. The model was carried on 664 records of CHB. Results. 16 features were selected for the syndrome of Damp Heat in the Liver and Gallbladder (DHLG), 20 features were selected for the syndrome of Liver qi Stagnation and Spleen Deficiency (LSSD) and 13 features were selected for the syndrome of Yin Deficiency of Liver and Kidney (YDLK). The lowest average accuracy was 80.52% using logitboost, whereas the accuracy of HISD was 85% for unrecognized cases of CHB. Conclusion. Our method extracts the relevant symptoms and signs for each syndrome, recognizes the main syndrome and accompanying syndromes, and improves its recognition accuracy.
Keywords :
diseases; feature selection; kidney; liver; medical computing; patient diagnosis; probability; CHB; DHLG; HISD model; LSSD; TCM; YDLK; Yin deficiency-of-liver-and-kidney; accompanying syndromes; chronis hepatitis B; damp heat-in-the-liver-and-gallbladder; feature selection; hybrid intelligent syndrome diagnosis model; liver qi stagnation-and-spleen deficiency; main syndrome; patient syndrome; probability-classification methods; recognition accuracy; traditional Chinese medicine; Accuracy; Educational institutions; Feature extraction; Liver; Medical diagnostic imaging; Mouth; Tongue; Traditional Chinese medicine; data mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on
Conference_Location :
Shanghai
Type :
conf
DOI :
10.1109/BIBM.2013.6732629
Filename :
6732629
Link To Document :
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