Yubin Wang
ABSTRACT
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.
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Index Terms
- Identification of Cardiovascular Diseases Based on Machine Learning
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