Research And Implementation Of Intelligent TCM Auxiliary Diagnosis And Treatment System

The progress and development of modem science and technology accelerate the digitization process of medical information,and the medical system is gradually sound and complete.Data mining technology is widely used in the medical field.As the treasure of the Chinese medicine of traditional Chinese medicine,after thousands of years of medical practice,gradually formed and developed into a unique medical system,rich experience of complete medical treatment,but as the experience medicine,TCM diagnosis is difficult to form a specific diagnostic criteria,diagnostic experience for diagnosing the demand is higher,in the process of application for promotion.Therefore,it is of great academic significance and application value to comprehensively apply various data mining methods to carry out the basic theoretical research of TCM assisted diagnosis on the basis of TCM clinical data.In this paper,based on the above issues,the application of data mining technology in the auxiliary diagnosis of traditional Chinese medicine research,the theory and application of data mining algorithms are analyzed,mainly studies the basic theory of neural network,mathematical modeling,algorithm optimization,process and model based on four different neural network simulation to predict the sample set,analyzes the advantages and disadvantages of different network,in view of the problems when mixed forecasting accuracy is not high,presents an optimization method based on DS evidence theory.At the same time,correlation analysis is carried out on the treatment schemes in traditional Chinese medieine eases.By comparing the running speed and correlation results of the classical Apriori correlation algorithm and fp-growth correlation algorithm,the advantages and disadvantages of the two correlation algorithms in the application process are explored,and the correlation algorithm with better performance is selected for implementation in the system.These two parts lay a theoretical foundation for the algorithm design of the intelligent TCM auxiliary diagnosis and treatment system.Finally,based on the improvement of DS evidence theory to optimize the neural network prediction model as the main method of TCM disease prediction,using FP-growth correlation algorithm as the main method of treatment is recommended,designed based on intelligent aided diagnosis of traditional Chinese medicine of the Django framework system,concrete implementation of disease prediction,treatment recommendations and other auxiliary diagnostic function and patient infornation,medical information,records of basic data management capabilities.