The Diagnosis And Treatment Regular Of Febrile Disease In TCM Mining Model Research Based On Improved Apriori Algorithm

Traditional Chinese Medicine(TCM) is the experience crystallization of struggle between our progenitors and the diseases. After several thousand years of continuous development, TCM has accumulated a large number of authorities and medical records which constituted the foundation of the instruction that how to act appropriately to the situation for TCM workers. How to analyze the data of TCM, to quest its regular and to form the system of deductive inference that is similar to western medicine are the difficulties of the current TCM research. The research situation of the data mining applied in the TCM and the development situation of the association rules data mining algorithm are firstly introduced in the paper. One of the association rules classical algorithm, apriori algorithm, is emphatically studied. Then the multi-dimensional association rules and numeric association rules are thoroughly analyzed. Furthermore, due to the limitation and the insufficiency of present association rules algorithm, the kind of multi-dimensional numeric association rules algorithm based on the relational database is improved to expand the applicable scope and raise the efficiency of execution drastically. Finally, in view of the insufficiency of current data mining in the TCM research application, a information excavation model of the febrile disease in TCM medical records is proposed and applied in the comprehensive system knowledge excavation of the medical record information by using the "dialectical treats" TCM principle and the improving algorithm mentioned above. The experiment results show that the efficiency of the improving algorithm is obviously higher than that of the traditional apriori algorithm and the expansion of the former is also superior to the later. The model excavation result is completely consistent with the existing conclusions of the febrile disease research in TCM, which has certain instruction function for diagnosing and treating clinical work as well as the teaching of the febrile disease in TCM. Since the similar rules outputted by the proposed model are abundant, how to reorganize and utilize these rules is the emphasis of our future work.