Identification of Cardiovascular Diseases Based on Machine Learning

Cardiovascular disease has been a major killer threatening human life and health. This paper is devoted to studying the characteristics of patients with cardiovascular diseases and classifying them by physical examination indicators. K-means algorithm is uesd to analyze the characteristics and xgboost is used to form a better classifier. The effect of the models are evaluated by relevant indexes. The experimental results show that, compared with normal people, patients with cardiovascular diseases have three characteristics: an older age, higher blood pressure, and heavier weight. Meanwhile, systolic blood pressure, cholesterol, and age are three important indicators for the classification of cardiovascular diseases.