Machine learning for heart disease diagnoses:A comparative study

摘要：

　　Background Heart disease diagnosis is an important issue in the world.It has great significance to study the method of helping doctors improve the diagnostic accuracy of heart disease.Methods RBF-DDA Artificial Neural Network, Support Vector Machine,Random Forest were used to diagnose the subjects sick or not.And compare their performance.Results Random Forest has the best performance, Support Vector Machine followed, RBF-DDA Artificial Neural Network is the worst.Conclusion Random Forest and Support Vector Machine have a good effect in heart disease diagnosis.And Random Forest is much better.

关键词： Decision support system Machine learning Heart disease Random Forest Support Vector Machine RBF DDA

作者: Kai Pang Sen Yang Jianxing Yu Yang Yu Hui pang Yuchun Tao

作者单位: Epidemiology and Statistics, School of Public Health, Jilin University

会议类型: 国内会议

会议名称: 2016年中国生物统计学术年会

会议地点: 天津

会议语种:英文

页码: 209-218

在线出版日期: 2016-07-26（万方平台首次上网日期，不代表论文的发表时间）