Research On The Application Of Data Mining In Medical Diagnosis System Of Heart Disease

Heart disease is a very common high-incidence disease.The major types of diseases are rheumatic heart disease,congenital heart disease,hypertension heart disease,myocarditis,coronary heart disease,etc.,heart disease has become one of the main factors leading to human death.At present,the prevalence of heart disease is becoming younger and more attention has been paid to medical research.Because of the variety of pathological types of heart disease and the variety of factors affecting it,how to improve the medical diagnosis of heart disease and to intervene and treat it earlier is an urgent problem to be solved.With the development of medical diagnosis system for heart disease,more and more people pay attention to it,and the research on heart disease has become a hot research field of cross-disciplinary research.Through the understanding of all kinds of data,the classification algorithm of data mining algorithm based on data mining technology has carried on a lot of research to the heart disease medical diagnosis system,which mainly focuses on the neural network algorithm.Support vector machine algorithm and so on.Based on two algorithms,in this paper,the decision tree algorithm is added to compare with the decision tree algorithm.Referring to the advantages and disadvantages of the three classical classification algorithms,an optimized classification algorithm,Co-Svm.,is proposed in this paper.Establishment of Heart Disease diagnosis based on in-situ data Mining algorithm Classifier,which aims at heart disease diagnosis,explores which of the four algorithms is more suitable and optimizes them.The causes,influencing factors and acquired data of heart disease are briefly explained,so that the accuracy and scientificity of the data can be known,and the authenticity and reliability of establishing the clinical diagnosis model of heart disease are further improved.Carry on the digital data information processing,aim at four kinds of different data effective mining,expand the parameter calculation way and the modern integration way effective acquires the classification method,The most effective clinical diagnostic classification tool for heart disease was selected by authoritative clinical medical evaluation.In this paper,the Heart Disease heart disease clinical data set in the(University of Californialrvine)machine learning database of the University of California,Irvine is taken as the research object,and the decision tree algorithm,the neural network algorithm,respectively,are selected as the object of study.Support vector machine(SVM)algorithmand Co-SVM algorithm are used to establish heart disease diagnosis classifier.The optimal classification algorithm,Co-SVM algorithm,is selected according to the comparison and analysis of the experimental results.The experimental results show that the proposed Co-SVM algorithm has higher accuracy than the other three classical algorithms.The effectiveness of the Co-SVM algorithm is verified by a variety of evaluation results.Through the application of Co-SVM algorithm in the medical diagnosis system,it is helpful to assist doctors to make more accurate and accurate diagnosis of the disease.