Bayesian Based Information Fusion and Its Application in Heart Disease Diagnosis
Xu Ma · Industrial Engineering and Management · 2013
To raise the rate of accuracy and reduce the misdiagnosis rate in computer aided medical diagnostic system,a hybrid model based on Bayesian networks learning and case based reasoning was presented.In this model,CBR(cased based reasoning)was adopted as the method to index cases,and Bayesian network was used as the tool of data mining.Relations of diagnosis attributes were obtained from case samples,and similarity evaluation function of CBR was built.With the similarity evaluation function,CBR index the case database,so that the most similar case could be obtained.Then,with a case of heart disease diagnosis,the effect of the hybrid model was illuminated.