Analyzes the risk of cardiovascular disease

Abstract

Currently, cardiovascular disease has a population risky for many diseases. The general public can analyze preliminary data by yourself can be examination and treatment in a timely.
The research aims develop to a model analyzes the risk of cardiovascular disease with a neural network algorithm and decision tree algorithm and develop program analyzes the risk of cardiovascular disease. The experiment create a model found that the best algorithm can anticipated classification of the risk of cardiovascular disease by the both algorithms use WEKA program is tools in the  analysis and Classified information for the best algorithm.  It use in developing by the variables in the data classification. Classification of data create model has 5 attribute include Blood pressure, smoking and diabetes, sex and age by save date from general public 493 sets in Na Oa sub-district, Muang district, Loei Province. The survey data was audited by Correctional health experts Si Song Rak Health Promotion Hospital check accurate Data before create a model. The experiment create a model found that the best algorithm can anticipated classification of the risk of cardiovascular disease. It is neural network algorithm which identified correctly the on maximum 97.2973 percent. Decision tree algorithm can identified correctly the program on 95.3347 After that, a model of neural network algorithm and decision tree algorithm develop to a program help analysis the risk of cardiovascular disease. So, the test of develop program found that neural network model can anticipated correctly the risk on percent 99.5