Research on risk factors of heart disease based on data mining

In recent years, the incidence of cardiovascular disease has been on the rise, and the causes have gradually become more complex, so it is urgent to intervene in the diagnosis and treatment of heart disease. In this paper, 251,505 survey responses from BRFSS were selected to analyze the cardiology dataset using the Logistic model and the C5.0 decision tree model. The results show that the occurrence of heart disease has a strong relationship with hypertension, smoking, stroke history, gender, and age, which has certain practical significance for the prediction and diagnosis of heart disease.