深度神经网络模型在心电图中的应用进展  

Application of deep neural network models to the electrocardiogram

作　　者：周天[1] ZHOU Tian(Department of Electrocardiogram,the First College of Clinical Medical Science,China Three Gorges University,Yichang Central People’s Hospital,Yichang,Hubei 443000,P.R.China)

机构地区：[1]三峡大学第一临床医学院,宜昌市中心人民医院心电诊断科,湖北宜昌443000

出　　处：《华西医学》2023年第1期126-129,共4页West China Medical Journal

摘　　要：心电图是一种无创、廉价、便捷的诊断心血管疾病和评估心血管事件风险的检查方法。尽管心电图检查已具备明确的标准化操作及流程,但由于诊断经验的不同,即便是训练有素的医生对心电图的解释也可能存在主观偏差。近年来,人工智能通过建立深度神经网络模型,已经成为一种自动分析医疗数据的强大工具,在CT、MRI、超声以及心电图等医学图像诊断领域得到了广泛应用。该文主要介绍深度神经网络模型在心电图诊断和预测心血管疾病方面的应用进展,并讨论其局限性和应用前景。Electrocardiogram(ECG)is a noninvasive,inexpensive,and convenient test for diagnosing cardiovascular diseases and assessing the risk of cardiovascular events.Although there are clear standardized operations and procedures for ECG examination,the interpretation of ECG by even trained physicians can be biased due to differences in diagnostic experience.In recent years,artificial intelligence has become a powerful tool to automatically analyze medical data by building deep neural network models,and has been widely used in the field of medical image diagnosis such as CT,MRI,ultrasound and ECG.This article mainly introduces the application progress of deep neural network models in ECG diagnosis and prediction of cardiovascular diseases,and discusses its limitations and application prospects.

关 键 词：深度神经网络模型 心电图 人工智能 

分 类 号：R540.41[医药卫生—心血管疾病]