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Application of artificial intelligence-enabled ECG in diagnosis of inherited arrhythmia |
SONG Wenhua, XIE Jiawei, LIU Tong |
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Abstract 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.
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[1] |
. [J]. JOURNAL OF PRACTICAL ELECTROCARDIOLOGY, 2022, 31(2): 144-146. |
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