The electrocardiogram is the most widely used diagnostic tool that records the electrical
activity of the heart and, therefore, its use for identifying markers for early diagnosis and …

In the recent decade, deep learning, a subset of artificial intelligence and machine learning,
has been used to identify patterns in big healthcare datasets for disease phenotyping, event …

Background The electrocardiogram (ECG) is one of the most commonly used diagnostic
tools in medicine and healthcare. Deep learning methods have achieved promising results …

Cardiovascular disease (CVD) is the leading cause of death worldwide, and coronary artery
disease (CAD) is a major contributor. Early-stage CAD can progress if undiagnosed and left …

Artificial intelligence for the electrocardiogram | Nature Medicine Skip to main content Thank
you for visiting nature.com. You are using a browser version with limited support for CSS. To …

Over the last decade, cardiovascular diseases (CVD's) are the leading cause of death
globally. Early prediction of CVD's can help in reducing the complications of high-risk …

Electrocardiogram (ECG) gives essential information about different cardiac conditions of
the human heart. Its analysis has been the main objective among the research community to …

The aim of this review was to assess the evidence for deep learning (DL) analysis of resting
electrocardiograms (ECGs) to predict structural cardiac pathologies such as left ventricular …

Widely developed for clinical screening, electrocardiogram (ECG) recordings capture the
cardiac electrical activity from the body surface. ECG analysis can therefore be a crucial first …

An electrocardiogram (ECG) is one of the most promising approaches used for the detection
and classification of cardiovascular diseases (CVDs) in recent years. This work reviewed …