Machine learning–powered, device-embedded heart sound measurement can optimize AV delay in patients with CRT-Reference-Cited by-同舟云学术

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Machine learning–powered, device-embedded heart sound measurement can optimize AV delay in patients with CRT

Published:2023-09 Issue:9 Volume:20 Page:1316-1324
ISSN:1547-5271
Container-title:Heart Rhythm
language:en
Short-container-title:Heart Rhythm

Author:

Westphal Philip,Luo Hongxing,Shahmohammadi Mehrdad,Prinzen Frits W.,Delhaas Tammo,Cornelussen Richard N.

Funder

Horizon 2020 Framework Programme

Horizon 2020

Medtronic

Publisher

Elsevier BV

Subject

Physiology (medical),Cardiology and Cardiovascular Medicine

Reference35 articles.

1. Cardiac-resynchronization therapy with or without an implantable defibrillator in advanced chronic heart failure;Bristow;N Engl J Med,2004

2. The effect of cardiac resynchronization on morbidity and mortality in heart failure;Cleland;N Engl J Med,2005

3. Non-responders to cardiac resynchronization therapy: the magnitude of the problem and the issues;Auricchio;Circ J,2011

4. Understanding non-response to cardiac resynchronisation therapy: common problems and potential solutions;Sieniewicz;Heart Fail Rev,2019

5. Determination of the optimal atrioventricular delay in DDD pacing: comparison between echo and peak endocardial acceleration measurements;Ritter;Europace,1999

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Update on the Use of Artificial Intelligence in Cardiovascular Medicine;Hearts;2024-02-09

2. Frontiers in conduction system pacing: treatment of long PR in patients with heart failure;European Heart Journal Supplements;2023-11

3. Machine learning and the automated optimization of cardiac device parameters;Heart Rhythm;2023-09

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