Using artificial intelligence-enabled electrocardiogram to predict cardiac resynchronization therapy outcomes of left bundle branch area pacing

被引：4

作者：

Chen, Jingjing ^{[1
,2
]}

Ezzeddine, Fatima M. ^{[2
]}

Liu, Xiaoke ^{[3
]}

Munoz, Freddy Del-Carpio ^{[2
]}

Friedman, Paul ^{[2
]}

Cha, Yong-Mei ^{[2
]}

机构：

[1] Guizhou Med Univ, Affiliated Hosp, Dept Cardiovasc Med, Guiyang, Peoples R China

[2] Mayo Clin, Dept Cardiovasc Med, Rochester, MN USA

[3] Mayo Clin, Dept Cardiovasc Med, La Crosse, WI USA

来源：

EUROPACE | 2023年 / 26卷 / 01期

关键词：

Artificial intelligence; Cardiac resynchronization therapy; Electrocardiogram; Heart failure; Left bundle branch area pacing;

D O I：

10.1093/europace/euae007

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

[No abstract available]

引用

页数：2

共 5 条

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[3]

Burri H, 2023, EUROPACE, V25, P1208, DOI 10.1093/europace/euad043

[4]

Svennberg E., 2023, Europace, V25, peuad176

[5] Artificial intelligence-enabled electrocardiograms for identification of patients with low ejection fraction: a pragmatic, randomized clinical trial [J].

Yao, Xiaoxi ;

Rushlow, David R. ;

Inselman, Jonathan W. ;

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Thacher, Thomas D. ;

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Bernard, Matthew E. ;

Rosas, Steven L. ;

Akfaly, Abdulla ;

Misra, Artika ;

Molling, Paul E. ;

Krien, Joseph S. ;

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NATURE MEDICINE, 2021, 27 (05) :815-+

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