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从使用深度学习的心电图来识别心律失常和纤维化风险的中心脱落,使用深度学习

Geoffrey H Tison1,2, Sean Abreau1, Joshua Barrios1

  • 1Cardiovascular Division, Department of Medicine, University of California-San Francisco, San Francisco, California, USA.

JACC. Advances
|November 8, 2023
PubMed
概括

使用心电图 (ECG) 的机器学习可以识别患有心交脱落 (MVP) 的患者,这些患者有复杂腹腔外垂 (ComVE),死亡和心脏纤维化风险. 这项技术有助于选择高风险的MVP患者进行更密切的监测.

关键词:
人工智能是一种人工智能.电脑 计算机 计算机 计算机超声心电图 (Echocardiography) 是一种心声回声仪.膜性心脏病是一种心脏病.

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