Novel ECG features and machine learning to optimize culprit lesion detection in patients with suspected acute coronary syndrome.
Background: Novel temporal-spatial features of the 12‑lead ECG can conceptually optimize culprit lesions' detection beyond that of classical ST amplitude measurements. We sought to develop a data-driven approach for ECG feature selection to build a clinically relevant algorithm for real-time detecti...
| Publicado en: | Journal of Electrocardiology Vol. 69; pp. 31 - 38 |
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| Autores principales: | , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
W B Saunders
2021 Supplement
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| Acceso en línea: | Ver este registro en EBSCOhost |