Distinct ECG phenotypes identified in hypertrophic cardiomyopathy using machine learning associate with arrhythmic risk markers
<p>Aims: Ventricular arrhythmia triggers sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM), yet electrophysiological biomarkers are not used for risk stratification. Our aim was to identify distinct HCM phenotypes based on ECG computational analysis, and characterize differences...
Κύριοι συγγραφείς: | Lyon, A, Ariga, R, Minchole, A, Mahmod, M, Ormondroyd, E, Laguna, P, de Freitas, N, Neubauer, S, Watkins, H, Rodriguez, B |
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Μορφή: | Journal article |
Έκδοση: |
Frontiers Media
2018
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Παρόμοια τεκμήρια
Παρόμοια τεκμήρια
-
Risk stratification in hypertrophic cardiomyopathy based on QRS and
T wave morphological biomarkers identifies three phenotypic
subgroups
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The arrhythmic substrate of hypertrophic cardiomyopathy using ECG imaging
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The arrhythmic substrate of hypertrophic cardiomyopathy using ECG imaging
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Electrocardiogram phenotypes in hypertrophic cardiomyopathy caused by distinct mechanisms: apico-basal repolarization gradients vs. Purkinje-myocardial coupling abnormalities
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Extraction of morphological QRS-based biomarkers in hypertrophic cardiomyopathy for risk stratification using L1 regularized logistic regression
ανά: Lyon, A, κ.ά.
Έκδοση: (2016)