Classification of Cardiovascular Disease Using AdaBoost Method

The paper is devoted to diagnosing patients with cardiovascular disease. To determine the disease in medical diagnostics, statistical methods are most often used Data Mining, which with large amounts of information and complex relationships can give more accurate estimates, especially with a large number of similar characteristics. The machine learning model for cardiovascular disease classification based on AdaBoost method have been developed using Python programming language. We used dataset of 68783 patients with suspicious of cardiovascular disease. The results of the simulation show enough accuracy for using it in Public Health practice. Implementation of information system can increase diagnosing the cardiovascular disease by medical workers.