Wavelet Based Machine Learning Algorithms to Enhance Cardiovascular Disease Diagnosis

被引:0
|
作者
Kottou, Rafaela [1 ]
Pegkou-Christofi, Veronica [1 ]
机构
[1] Western Connecticut State Univ, Math Dept, Danbury, CT 06810 USA
来源
2019 6TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE (CSCI 2019) | 2019年
关键词
Heart Disease; Wavelet Transforms; Neural Network; Long Short Term Menwry; Support Vector Machines;
D O I
10.1109/CSCI49370.2019.00273
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The heart is arguably one of the most vital organs of the human body, pumping blood and nutrients to all other organs. In recent years, the heart has become a popular topic of discussion as the amount of cardiovascular deaths continues to grow at an alarming rate worldwide. Early detection of such diseases plays a crucial role in resolving this health crisis. However, human errors combined with a lack of doctor availability often hinder accurate detection of heart diseases, especially in developing countries. In this study, we have developed a unique combination of machine learning and Wavelet Transforms as a means of detecting heart disease. In the future, this artificial intelligence tool could be implemented worldwide, allowing individuals to record their own heart beat and receive immediate diagnosis.
引用
收藏
页码:1464 / 1469
页数:6
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