PACEMAKER IMPLANTATION FOLLOWING TAVR: USING MACHINE LEARNING TO OPTIMIZE RISK STRATIFICATION-Reference-Cited by-同舟云学术

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PACEMAKER IMPLANTATION FOLLOWING TAVR: USING MACHINE LEARNING TO OPTIMIZE RISK STRATIFICATION

Published:2020-03 Issue:11 Volume:75 Page:1478
ISSN:0735-1097
Container-title:Journal of the American College of Cardiology
language:en
Short-container-title:Journal of the American College of Cardiology

Author:

Truong Vien T.,Wigle Matthew,Bateman Emma,Pallerla Akhil,Ngo Tam N.M.,Beyerbach Daniel,Kereiakes Dean,Shreenivas Satya,Tretter Justin,Palmer Cassady,Mazur Wojciech,Chung Eugene

Publisher

Elsevier BV

Subject

Cardiology and Cardiovascular Medicine

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. MemGCN: memory-augmented graph neural network for predict conduction disturbance after transcatheter aortic valve replacement;Applied Intelligence;2023-09-08

2. Towards patient-specific prediction of conduction abnormalities induced by transcatheter aortic valve implantation: a combined mechanistic modelling and machine learning approach;European Heart Journal - Digital Health;2021-08-20

3. Machine Learning Algorithms for Prediction of Permanent Pacemaker Implantation After Transcatheter Aortic Valve Replacement;Circulation: Arrhythmia and Electrophysiology;2021-03

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