Prediction System Of Cardiovascular Disease Based On BP Neural Network Research And Implementation

At present,the cooperation between computer technology and medical field is becoming closer and closer.However,the application of computer technology in disease diagnosis and prediction is in the development stage.For the timely detection of cardiovascular diseases,early treatment and the reduction of misdiagnosis and missed diagnosis,etc.However,there are still some problems in the study of disease prediction.One is that computers are mostly used for disease detection rather than prediction.Knowledge mining technology is often used to process images,and ultimately needs to be judged manually by the doctor.Second,such as the symptoms of pre-disease and symptoms have the same.Similar,and experts in different fields of disease based on long-term knowledge accumulation and clinical experience,thus for the same clinical symptoms of the diagnosis and treatment of different disease results.In order to improve the level of medical treatment and to realize the prevention and diagnosis of diseases,this paper studies the common indexes of cardiovascular diseases,and combines the characteristics of neural network adaptive.The application of BP neural network algorithm in cardiovascular prediction can effectively reduce the error of artificial diagnosis and improve the accuracy of disease prediction.The research and implementation of cardiovascular prediction system based on BP neural network include:1.Combining the filtering and encapsulation attribute reduction algorithms,studying the feature selection methods,and comparing the filtering and encapsulation based feature selection algorithms,referring to the existing prediction results of cardiovascular and Cardiovascular diseases,In order to reduce the high dimensional feature of disease data,the indexes of cardiovascular disease prediction system were collected and cleaned.In order to reduce redundancy and improve system performance,an attribute reduction algorithm based on fusion filtering and encapsulation is proposed to solve the feature selection problem.2.the construction of prediction model based on BP neural network.This paper enumerates several kinds of disease prediction methods and makes analysis and comparison,and finally determines that the neural network prediction method is applied to cardiovascular disease prediction.According to the experimental data and environment that has been mature and applied in academic circles at present,a cardiovascular prediction model based on BP neural network is built.The training and forecasting process of BP neural network are studied in this paper.In the course of training,the weight value is adjusted constantly,so that the error of disease prediction model is small.3.The design and implementation of the cardiovascular prediction system.According to the existing disease prediction model and the BP neural network model constructed in the paper,the demand analysis and functional positioning of the cardiovascular prediction system are carried out.The general framework of the disease prediction system is built,and the disease prediction system is designed and implemented,which provides a reference method for the prediction of cardiovascular and cardiovascular diseases.