Predicting electrical storms by remote monitoring of implantable cardioverter-defibrillator patients using machine learning-Reference-Cited by-同舟云学术

Predicting electrical storms by remote monitoring of implantable cardioverter-defibrillator patients using machine learning

Published:2018-11-30 Issue:2 Volume:21 Page:268-274
ISSN:1099-5129
Container-title:EP Europace
language:en
Short-container-title:

Author:

Shakibfar Saeed¹,Krause Oswin¹,Lund-Andersen Casper²,Aranda Alfonso³,Moll Jonas¹,Andersen Tariq Osman¹,Svendsen Jesper Hastrup²⁴,Petersen Helen Høgh²,Igel Christian¹

Affiliation:

1. Department of Computer Science, University of Copenhagen, Universitetsparken 5, Copenhagen 2100, Denmark

2. Department of Cardiology, The Heart Centre, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark

3. Medtronic, Medtronic Bakken Research Center, Maastricht, The Netherlands

4. Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark

Funder

Innovation Fund Denmark

Publisher

Oxford University Press (OUP)

Subject

Physiology (medical),Cardiology and Cardiovascular Medicine

Link

http://academic.oup.com/europace/article-pdf/21/2/268/27721220/euy257.pdf

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2. 2013 ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology Foundation/American Heart Association Task Force on practice guidelines;Yancy;Circulation,2013

3. Electrical storm in patients with transvenous implantable cardioverter-defibrillators: incidence, management and prognostic implications;Credner;J Am Coll Cardiol,1998

4. Is electrical storm in ICD patients the sign of a dying heart? Outcome of patients with clusters of ventricular tachyarrhythmias;Greene;Europace,2000

5. Electrical storm in patients with an implantable defibrillator: incidence, features, and preventive therapy: insights from a randomized trial;Hohnloser;Eur Heart J,2006

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