A method to screen left ventricular dysfunction through ECG based on convolutional neural network.
Jin-Yu SunYue QiuHong-Cheng GuoYang HuaBo ShaoYu-Cong QiaoJin GuoHan-Lin DingZhen-Ye ZhangLing-Feng MiaoNing WangYu-Min ZhangYan ChenJuan LuMin DaiChang-Ying ZhangRu-Xing WangPublished in: Journal of cardiovascular electrophysiology (2021)
Our results demonstrate that a well-trained CNN algorithm may be used as a low-cost and noninvasive method to identify patients with left ventricular dysfunction.
Keyphrases
- convolutional neural network
- left ventricular
- low cost
- deep learning
- hypertrophic cardiomyopathy
- heart failure
- cardiac resynchronization therapy
- oxidative stress
- acute myocardial infarction
- machine learning
- aortic stenosis
- mitral valve
- left atrial
- high throughput
- heart rate variability
- heart rate
- coronary artery disease
- percutaneous coronary intervention
- blood pressure
- body composition
- ejection fraction