Application Research Of Discriminant And Cluster Method In Clinical Acupuncture Data Analysis

Traditional Chinese medicine carries medical experience and theoretical knowledge of the Chinese nation since ancient times, which are the Chinese nation irreplaceable treasures. How to make use of modern methods of data analysis to mine the inherent laws, relevant knowledge and experiences of acupuncture clinical treatments, so as to provide the aided analysis basis for scientific theories of acupuncture clinical treatment, is an important field worthy of exploration, research and analysis.In this paper, discriminant analysis and cluster analysis methods are used for the research and application of analysis methods to the acupuncture clinical data. A Chinese medicine acupuncture information base system has been designed and implemented based on Java EE software framework, B/S architecture pattern and third normal form in database normalization, two types of statistical analysis algorithm and a demonstrated platform of the analyzed results have been provided for the scientific analysis research of acupuncture clinical data. The major research contents and innovations in this paper are summarized as the followings:1) Application research of discriminant analysis methods. A kind of classification rule for curative effect has been designed by analyzing the acupuncture treatment cases described in the literatures. Thereby, the acupuncture treatment samples described in the literatures can be processed to be discriminated for classification and to be entrusted for the different comprehensive curative effects, including the curative effect levels of acupuncture points and treatment, through the discriminant rule built by the discriminant analysis algorithm.2) Application research of cluster analysis methods. Proposed an Euclid Distance of combining acupuncture treatment differences and the comprehensive curative effect differences, to classify the sample set of data based on the similarity of the clinical sample data acupoint field, a clustering analysis algorithm has been designed and realized by programming that can divide the clinical sample data into relatively homogeneous samples’ classifications.3) A traditional Chinese medicine acupuncture (referred as TCM below) information base system and its analysis functions, have been designed and implemented. The system has the application functions which can be processed to retrieve and manage of literature resources, medical resources, user resources and e-book resources. The statistic analysis and displaying’s of the analysis results can be easily processed for the stored acupuncture treatment samples through the menu selection and parameters’ configuration.The achievements researched in this paper were obtained by studying, designing and programming practices under the background of strong collaborations of researchers from Shanghai Research Institute of Acupuncture and Meridian, and the acupuncture clinical sample data provided by them. The application methods of discriminant analysis and cluster analysis in the acupuncture clinical treatment sample data analysis are given in this paper, the analyzed effects are good. Similar research results are still rarely reported at present.