Electrocardiogram (ECG) signal compression techniques are essential for the efficient storage, transmission and real‐time processing of cardiac data. Advanced methods utilising discrete wavelet ...

Heart disease remains the leading cause of death worldwide, and although electrocardiography (ECG) is critical for diagnosis, interpreting ECG signals requires extensive training. Current machine ...

Accelerates development of personalized cardiac AI on the HeartBeam platform for wellness and clinical applications, including assessing heart attack risk ・Combines Mount Sinai’s world-class AI and ...

Through a deep-learning model, researchers have shown that ordinary ECG images can be leveraged to identify patients with an LV ejection fraction below 40%. Their approach also appears able to ...

Please provide your email address to receive an email when new articles are posted on . Algorithms to improve ECG interpretability received FDA clearance. The solution is designed to reduce noise ...

The electrocardiogram (ECG) is used to diagnose and monitor a multitude of conditions affecting the heart. More than just a measure of pulse rate, the ECG reveals the complex electrical activity of ...

Samsung Galaxy smartwatches could benefit from continuous monitoring for heart conditions, judging by a new patent filing from the tech giant. While current devices like the Galaxy Watch 6 enable ...

Sudden cardiac events (SCEs) are the leading cause of line-of-duty deaths (LODDs) among firefighters in the United States, so it is obvious why there is such an appeal for electrocardiogram (ECG) ...

An artificial intelligence (AI) algorithm has shown it is able to distinguish between healthy White and Black people using only their ECG readings. However, this finding only held true in adults with ...