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...
Main Authors: | Lyon, A, Ariga, R, Minchole, A, Mahmod, M, Ormondroyd, E, Laguna, P, de Freitas, N, Neubauer, S, Watkins, H, Rodriguez, B |
---|---|
Format: | Journal article |
Izdano: |
Frontiers Media
2018
|
Podobne knjige/članki
-
Risk stratification in hypertrophic cardiomyopathy based on QRS and
T wave morphological biomarkers identifies three phenotypic
subgroups
od: Lyon, A, et al.
Izdano: (2016) -
The arrhythmic substrate of hypertrophic cardiomyopathy using ECG imaging
od: Chow, J, et al.
Izdano: (2024) -
The arrhythmic substrate of hypertrophic cardiomyopathy using ECG imaging
od: Ji-Jian Chow, et al.
Izdano: (2024-08-01) -
Electrocardiogram phenotypes in hypertrophic cardiomyopathy caused by distinct mechanisms: apico-basal repolarization gradients vs. Purkinje-myocardial coupling abnormalities
od: Lyon, A, et al.
Izdano: (2018) -
Extraction of morphological QRS-based biomarkers in hypertrophic cardiomyopathy for risk stratification using L1 regularized logistic regression
od: Lyon, A, et al.
Izdano: (2016)