摘要
Abstract
Myocardial Infarction(MI)is a life-threatening emergency in cardiovascular disease.Early detection and accurate classification are crucial.12 lead ECG monitors the electrical activity of the heart from multiple perspectives,which has an important influence on the myocardial infarction classification.However,when the existing classification models deal with the problems caused by 12 lead information redundancy,the proposed solutions are not considered enough,which will lead to the loss of important leads and char-acteristic information.In addition,these methods do not fully consider the correlation between 12 lead and myocardial infarction,or only focus on the correlation of single lead,which will lead to the model and MI are not closely related.To solve the above problems,we propose a myocardial infarction classification model based on improved discarding and dual channel fusion.The model uses an improved adaptive discard algorithm(DroSet)to effectively solve the problem of redundant information caused by leads.At the same time,combined with medical knowledge and basic theory,we analyze the sensitivity and correlation between lead and myocardial infarction,and divide it into leading myocardial infarction lead and auxiliary myocardial infarction lead.The experimental results show that the classification accuracy of the proposed model on ptbxl data set reaches 99.15％,which proves that it not only has excellent classification performance,but also is suitable for the location of myocardial infarction in practical application.关键词
心肌梗死分类/12导联心电图/双通道融合/自适应丢弃Key words
myocardial infarction classification/12 lead electrocardiogram/12 lead ECG/dual channel fusion/adaptive discard分类
信息技术与安全科学
