Deep Learning for Myocardial Infarction Detection using Electrocardiogram Images: A Systematic Review

Myocardial infarction has been one of the leading causes of global mortality. Electrocardiograms (ECG) are the standard diagnostic tool; however, even among medical experts, the accuracy of ECG-supported diagnoses varies. To improve diagnostic accuracy, deep learning has emerged as a promising approach. Although numerous studies demonstrate its potential, the field lacks a unified characterization of state-of-the-art methods using ECG images. This systematic review addresses this gap by analyzing and synthesizing research efforts on deep learning models trained on ECG images for myocardial infarction detection.