Acute Myocardial Infarction: Analysis of the ECG Using Artificial Neural Networks

Abstract

This paper presents a neural network classifier for the diagnosis of acute myocardial infarction, using the 12-lead ECG. Features from the ECGs were extracted using principal component analysis, which allows for a small number of effective indicators. A total of 4724 pairs of ECGs, recorded at the emergency department, was used in this study. It was found (empirically) that a previous ECG, recorded on the same patient, has a small positive effect on the performance for the neural network classifier.