Functional feature extraction and validation from twelve-lead electrocardiograms to identify atrial fibrillation
Abstract Background Deep learning methods on standard, 12-lead electrocardiograms (ECG) have resulted in the ability to identify individuals at high-risk for the development of atrial fibrillation. However, the process remains a “black box” and does not help clinicians in understanding the electroca...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-02-01
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| Series: | Communications Medicine |
| Online Access: | https://doi.org/10.1038/s43856-025-00749-2 |
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