A Review of Automated Methods for Detection of Myocardial Ischemia and Infarction Using Electrocardiogram and Electronic Health Records

摘要: There is a growing body of research focusing on automatic detection ischemia and myocardial infarction (MI) using computer algorithms. In clinical settings, MI are diagnosed electrocardiogram (ECG) recordings as well medical context including patient symptoms, history, risk factors—information that often stored in the electronic health records. The ECG signal inspected to identify changes morphology such ST-segment deviation T-wave changes. Some proposed methods compute similar features automatically while others use nonconventional wavelet coefficients. This review provides an overview have been this area, their historical evolution, publicly available datasets they used evaluate performance, details algorithms for EHR analysis. validation strategies performance also presented. Finally, paper recommendations future address shortcomings currently existing practical considerations make technical solutions applicable practice.