Improving ECG Classification Interpretability using Saliency Maps. (arXiv:2201.04070v1 [eess.SP])

Cardiovascular disease is a large worldwide healthcare issue; symptoms often
present suddenly with minimal warning. The electrocardiogram (ECG) is a fast,
simple and reliable method of evaluating the health of the heart, by measuring
electrical activity recorded through electrodes placed on the skin. ECGs often
need to be analyzed by a cardiologist, taking time which could be spent on
improving patient care and outcomes. Because of this, automatic ECG
classification systems using machine learning have been proposed, which can
learn …

arxiv classification interpretability maps