DocumentCode :
684738
Title :
A probabilistic neural network approach for BCTTCM classification
Author :
Zhibiao Li
Author_Institution :
Dept. of Comput. Sci., Jiangxi Univ. of Traditional Chinese Med., Nanchang, China
fYear :
2012
fDate :
7-9 Dec. 2012
Firstpage :
1
Lastpage :
4
Abstract :
In view of the limitations of classifying body constitutional type in traditional Chinese medicine (BCTTCM) with the traditional method, the probability neural networks (PNN) method was put forward. The characteristic parameters of BCTTCM were obtained with the median, and a PNN model was designed for BCTTCM classification. The PNN model was trained and tested using 30 samples, and it yields good classification accuracies for BCTTCM. The overall accuracy of the neural network was 95% in the training set. It was 80% in the validation set. It indicated that the model was effective and the method based on the PNN for BCTTCM classification is feasible.
Keywords :
learning (artificial intelligence); medicine; neural nets; pattern classification; probability; BCTTCM classification; PNN model; body constitutional type in traditional Chinese medicine; probability neural networks; Constitutional type in traditional Chinese medicine; classification; probabilistic neural networks;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Information Science and Control Engineering 2012 (ICISCE 2012), IET International Conference on
Conference_Location :
Shenzhen
Electronic_ISBN :
978-1-84919-641-3
Type :
conf
DOI :
10.1049/cp.2012.2324
Filename :
6755703
Link To Document :
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