Automatic Detection of Atrial Fibrillation from Single-Lead ECG Using Deep Learning of the Cardiac Cycle
Objective and Impact Statement. Atrial fibrillation (AF) is a serious medical condition that requires effective and timely treatment to prevent stroke. We explore deep neural networks (DNNs) for learning cardiac cycles and reliably detecting AF from single-lead electrocardiogram (ECG) signals. Intro...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
American Association for the Advancement of Science (AAAS)
2022-01-01
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| Series: | BME Frontiers |
| Online Access: | http://dx.doi.org/10.34133/2022/9813062 |