Melancholia diagnosis based on CMAC neural network approach

Authors:
Chin-pao Hung;Shi-Liang Yang
Affiliations:
Department of Electrical Engineering, National Chin-Yi University of Technology, Taiwan, R.O.C.;Taichung Hospital, Department of Health, Taiwan, R.O.C.
Venue:
NN'07 Proceedings of the 8th Conference on 8th WSEAS International Conference on Neural Networks - Volume 8
Year:
2007

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Abstract

In this paper, a preliminary result about the melancholia diagnosis scheme based on the analyses of depression inventory and the meridian energy of human body is proposed. Firstly, a large amount data obtained from hospital, recorded the patients depression inventory and the 12 sets meridian energy signals, are sieved out three groups patterns. Then, CMAC (Cerebellar Model Articulation Controller) neural network diagnosis architecture is constructed depending on the three groups disease patterns. Thirdly, the selected patterns were utilized to train the CMAC neural network. Finally, inputting the 12 sets meridian energy signals of human body into CMAC neural network, the finished training neural network can diagnose the possibility people with melancholia or not.