Artificial intelligence-enabled electrocardiogram screens low left ventricular ejection fraction with a degree of confidence.
Chun-Ho LeeWei-Ting LiuYu-Sheng LouChin-Sheng LinWen-Hui FangChia-Cheng LeeChing-Liang HoChih-Hung WangChin LinPublished in: Digital health (2022)
The deep learning model with a degree of confidence can provide advanced improvements in identifying left ventricular dysfunction and serve as a decision support and management-guided screening tool for prognosis.
Keyphrases
- artificial intelligence
- ejection fraction
- aortic stenosis
- deep learning
- left ventricular
- machine learning
- big data
- transcatheter aortic valve replacement
- hypertrophic cardiomyopathy
- convolutional neural network
- heart failure
- cardiac resynchronization therapy
- acute myocardial infarction
- aortic valve
- high throughput
- oxidative stress
- left atrial
- genome wide
- mitral valve
- acute coronary syndrome
- gene expression
- coronary artery disease
- single cell