Predicting ECG Age in 24-hour Holter Recordings of Heart Failure Patients
Recent advances in deep learning enable estimation of a patient’s "ECG age" from standard short-term 12-lead electrocardiogram (ECG). This study introduces sequential ECG age predictions in continuous 24-hour Holter ECG recordings of chronic heart failure (CHF) patients. Using publicly available dat...
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| Hauptverfasser: | , , , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
De Gruyter
2025-09-01
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| Schriftenreihe: | Current Directions in Biomedical Engineering |
| Schlagworte: | |
| Online-Zugang: | https://doi.org/10.1515/cdbme-2025-0240 |
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