Complex Systems Entropy Network and Its Application in Data Mining for Chinese Medicine Tumor Clinics
复杂系统熵网络方法及其在中医肿瘤临床数据挖掘中的应用

This study was aimed to investigate the method of data mining for complex Chinese medicine tumor clinics data. This paper puts forth complex systems entropy network for data mining in tumor clinics. A mutual information algorithm based random permutation test is proposed to assess the correlation of multi-variables and then complex network is established. Based on tumor clinical data (718 cases) collected, data mining was performed by statistical information of the complex network. The results showed that interaction effects among multi-variables were discovered by complex systems entropy network. A total of 116 pairs synergy variables and 14 core synergy cliques, 82 pairs antagonistic variables and 7 core antagonistic cliques were found after 718 cases data mining. The results, for the most part, correspond with the actual clinics. It was concluded that complex systems entropy network is suitable for analysis of interaction effects among multi-variables and data mining for complex Chinese medicine clinics.