Clustering of Chinese Herb Complexes with Adaptive Resonance Theory

[[abstract]]Traditional Chinese medicine includes thousands of herbs as remedies for sick people. These herbs make up more complex prescriptions further. In the past, the usage of herb prescriptions was decided by doctors’ experience. There was not any qualitative method for the purpose of understanding the application of herb prescriptions. Therefore, we propose a method to infer that function of herb, and build up scientific rules of functions for traditional Chinese medicine prescriptions. Adaptive Resonance Theory (ART) is a model of neural network. This network just use a data set composed of input vector and output vector. It’s simpleand stable. We use it to classify herb prescriptions according to the theory of channel entry. The feature vector of Chinese medicine consists of the attributes including nature, flavour and channel entries. The ART model is trained with known feature vector. Then it is used to infer the application of unknown medicinal herbs