Top stories on using computational modeling and artificial intelligence to uncover arrhythmogenic mechanisms and advance arrhythmia management.
作者信息
Trayanova Natalia A, Yin Minglang, Prakosa Adityo
机构信息
Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, Maryland; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland.
Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, Maryland.
出版信息
Heart Rhythm. 2024 Nov;21(11):2368-2369. doi: 10.1016/j.hrthm.2024.07.034.
Abstract
摘要
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Top stories on using computational modeling and artificial intelligence to uncover arrhythmogenic mechanisms and advance arrhythmia management.关于运用计算建模和人工智能揭示心律失常机制及推进心律失常管理的头条新闻。
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本文引用的文献
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Assessing the arrhythmogenic propensity of fibrotic substrate using digital twins to inform a mechanisms-based atrial fibrillation ablation strategy.使用数字孪生评估纤维化基质的致心律失常倾向，以制定基于机制的心房颤动消融策略。
Nat Cardiovasc Res. 2024 Jul;3(7):857-868. doi: 10.1038/s44161-024-00489-x. Epub 2024 Jun 18.
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Deep learning evaluation of echocardiograms to identify occult atrial fibrillation.用于识别隐匿性心房颤动的超声心动图深度学习评估
NPJ Digit Med. 2024 Apr 13;7(1):96. doi: 10.1038/s41746-024-01090-z.
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Electrophysiological effects of stretch-activated ion channels: a systematic computational characterization.牵张激活离子通道的电生理效应：系统的计算表征
J Physiol. 2024 Sep;602(18):4585-4604. doi: 10.1113/JP284439. Epub 2023 Sep 4.
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A multiscale predictive digital twin for neurocardiac modulation.用于神经心脏调制的多尺度预测性数字孪生。
J Physiol. 2023 Sep;601(17):3789-3812. doi: 10.1113/JP284391. Epub 2023 Aug 1.
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Machine learning for ECG diagnosis and risk stratification of occlusion myocardial infarction.机器学习在心电图诊断和闭塞性心肌梗死危险分层中的应用。
Nat Med. 2023 Jul;29(7):1804-1813. doi: 10.1038/s41591-023-02396-3. Epub 2023 Jun 29.
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