计算机工程与应用2025，Vol.61Issue(23)：59-71,13.DOI:10.3778/j.issn.1002-8331.2503-0022
心律失常和心肌梗死诊断中心电图智能分析方法研究综述
Review of Intelligent Analysis Methods for Electrocardiograms in Diagnosis of Arrhythmia and Myocardial Infarction
摘要
Abstract
Electrocardiogram(ECG)remains the gold standard for diagnosing arrhythmia and myocardial infarction(MI),offering advantages such as non-invasiveness,real-time monitoring,and portability,making it widely used in clinical prac-tice.Research on intelligent analysis of ECG for these conditions holds great significance.Firstly,this paper introduces commonly used ECG databases for arrhythmia and MI.Then it reviews recent advances in ECG intelligent analysis over the past three years,including manual feature extraction,convolutional neural networks and their variants,graph neural networks,self-supervised learning,federated learning,active learning,deterministic learning,and generative model.Subsequently,it conducts an in-depth analysis of these methodologies from perspectives including data scale,classifica-tion patterns,model comparisons,and model complexity.The study compares the requirements,advantages,disadvantages,interpretability,and application scenarios of different approaches.Finally,it summarizes existing limitations in areas such as data quality and imbalance issues,conflicts between model generalizability and interpretability,trade-offs between privacy protection and collaborative efficiency,mismatches between computational resources and clinical deployment.Feasible solutions are proposed to address these challenges.关键词
心电图(ECG)/心律失常(MI)/心肌梗死/智能诊断/深度学习Key words
electrocardiogram(ECG)/myocardial infarction(MI)/arrhythmia/intelligent diagnosis/deep learning分类
信息技术与安全科学引用本文复制引用
韩闯,范宝骐,余梦瑶,阙文戈..心律失常和心肌梗死诊断中心电图智能分析方法研究综述[J].计算机工程与应用,2025,61(23):59-71,13.基金项目
国家自然科学基金青年项目(62303427) （62303427）
河南省科技攻关项目(242102211018) （242102211018）
中原科技创新青年拔尖人才项目. （）
