基于深度学习的无症状心肌缺血动态心电图智能检测研究

Study on Intelligent Detection of Silent Myocardial Ischemia Dynamic Electrocardiogram Based on Deep Learning

动态心电图是无症状心肌缺血临床诊断最常用的检查之一,但人工分析工作量大,效率和准确率有限。基于深度学习技术,提出一种辅助医生智能分析无症状心肌缺血动态心电图的算法,以提高动态心电图分析准确率,降低心电图解释误诊率。

Dynamic electrocardiogram(ECG) is one of the most commonly used tests in the clinical diagnosis of silent myocardial ischemia,but manual analysis has a heavy workload,limited efficiency and accuracy.Based on deep learning technology,the paper proposes an algorithm to assist doctors in intelligent analysis of silent myocardial ischemia dynamic ECG,which greatly improves the accuracy of dynamic ECG analysis and reduces the misdiagnosis rate of ECG interpretation.