人工智能心电图在遗传性心律失常诊断中的应用  

Application of artificial intelligence-enabled ECG in diagnosis of inherited arrhythmia

作　　者：宋文华 谢家伟 刘彤[1] SONG Wenhua;XIE Jiawei;LIU Tong(Department of Cardiology,the Second Hospital of Tianjin Medical University,Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease,Tianjin Institute of Cardiology,Tianjin 300211,China)

机构地区：[1]天津医科大学第二医院心脏科天津市心血管病离子与分子机能重点实验室天津心脏病学研究所,天津300211

出　　处：《实用心电学杂志》2022年第1期28-31,共4页Journal of Practical Electrocardiology

摘　　要：随着多种致病基因的出现及变异,相应遗传性疾病的流行率也在逐年升高。潜在致病性变异的外显性往往不典型或仅在患者晚年才表现出来,导致遗传性心脏病的诊断趋于复杂化和延迟化。随着机器学习等新技术的开发和应用,人工智能成为个性化医学、医学成像和疾病诊断等诸多领域的有力工具。其中,人工智能心电图能特异性分析并总结遗传性心律失常患者心电图的特征性表现,有助于相关疾病的早期诊断。本文综述了人工智能心电图用于遗传性心律失常(主要包括先天性长QT综合征、Brugada综合征、儿茶酚胺敏感性多形性室速)诊断的最新研究进展。With the emerging and mutation of various pathogenic genes,the prevalence of corresponding genetic diseases also increases year by year. The penetrance of potentially pathogenic mutation is often atypical or the mutation manifests itself only in one’s later years,which tends to complicate and delay the diagnosis of genetic heart diseases. With the development and application of new technologies such as machine learning,artificial intelligence( AI) has become a powerful tool in many fields including personalized medicine,medical imaging,and disease diagnosis. By using AI,we can specifically analyze and summarize the characteristic manifestations of ECG in patients with genetic arrhythmias,contributing to the early diagnosis of related diseases. This paper reviews the latest research progress of AI-enabled ECG utilized in the diagnosis of inherited arrhythmias,mainly including congenital long QT syndrome,Brugada syndrome,and catecholaminergic polymorphic ventricular tachycardia.

关 键 词：人工智能 心电图 遗传性心脏病 心律失常 先天性长QT综合征 Brugada综合征 儿茶酚胺敏感性多形性室速 

分 类 号：R541.7[医药卫生—心血管疾病] R540.4[医药卫生—内科学]