Distinct ECG Phenotypes Identified in Hypertrophic Cardiomyopathy Using Machine Learning Associate With Arrhythmic Risk Markers-Reference-Cited by-同舟云学术

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Distinct ECG Phenotypes Identified in Hypertrophic Cardiomyopathy Using Machine Learning Associate With Arrhythmic Risk Markers

Published:2018-03-13 Issue: Volume:9 Page:
ISSN:1664-042X
Container-title:Frontiers in Physiology
language:
Short-container-title:Front. Physiol.

Author:

Lyon Aurore,Ariga Rina,Mincholé Ana,Mahmod Masliza,Ormondroyd Elizabeth,Laguna Pablo,de Freitas Nando,Neubauer Stefan,Watkins Hugh,Rodriguez Blanca

Funder

British Heart Foundation

Wellcome Trust

National Institute for Health Research

Publisher

Frontiers Media SA

Subject

Physiology (medical),Physiology

Reference48 articles.

1. Occurrence and frequency of arrhythmias in hypertrophic cardiomyopathy in relation to delayed enhancement on cardiovascular magnetic resonance;Adabag;J. Am. Coll. Cardiol.,2008

2. Laplacian eigenmaps for dimensionality reduction and data representation;Belkin;Neural Comput.,2003

3. Unsupervised feature selection for multi-cluster data;Cai,2010

4. Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. A statement for healthcare professionals from the Cardiac imaging committee of the council on clinical Cardiology of the American Heart Association;Cerqueira;Circulation,2002

5. Risk stratification for sudden cardiac death in hypertrophic cardiomyopathy: systematic review of clinical risk markers;Christiaans;Europace,2010

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