Research On Medical Database Based On Data Mining

According to clinical data as the research object,based on relevant knowledge of data mining,the use of several commonly used data mining methods of mass data generated on the medical collection,sorting,processing,analysis,processing the results of each method in the clinical data generated were compared,and combined with practical clinical experience and results,respectively,for each kind of data mining analysis of the obtained results are precise evaluation method.The main research contents are as follows:First,this paper first introduces the concept,process,method of data mining and the development of data mining technology and theory,then briefly introduced the classification and the basic idea of data mining;then introduces in detail the methods of data mining and its application;introduces and studies three kinds of important data mining analysis method,decision tree induction,association analysis and clustering,and the advantages and disadvantages of each method are analyzed and compared,finally,put forward the concrete application environment of each method and improvement suggestions.Based on the specific method of two,introduced in detail,and the research of data mining on massive data,is proposed based on clinical medicine on specific problems,respectively,three kinds of data mining methods for application of the above research and Analysis on the data,the method for each of the data mining results,Process,and the accuracy of evaluation and comparison of the advantages and disadvantages,so that each kind of data mining methods,in order to clinical medical problem specific and different treatment goals and requirements,using the best data mining methods,in order to improve the clinical medical work efficiency of the hospital.Three,based on the research background illustrates the background,the theoretical significance of mathematics among the data mining methods and technology applied to clinical medicine and practical significance.At the same time,summarizes the innovation points of this paper and theoretical framework.