Patent covers machine learning techniques for ECG denoising, rhythm classification, sample-level labelling, wearable cardiac monitoring, and report generation TORONTO, ON / ACCESS Newswire / June 23, ...

This study aims to establish an interpretable disease classification model via machine learning and identify key features related to the disease to assist clinical disease diagnosis based on a ...

This repository includes the code of the ECG-DualNet for ECG classification proposed in the paper Exploring Novel Algorithms for Atrial Fibrillation Detection by Driving Graduate Level Education in ...

The aim of this study is to analyze the performance of classifying stress and non-stress by measuring biosignal data using a wearable watch without interfering with work activities at work. An ...

Abstract: The 12-lead electrocardiogram (ECG) method can diagnose more cardiovascular disease than the single-lead method, but it is difficult to use in daily life because numerous electrodes must be ...

Laboratory of Data Science and Digital Inclusion, Institut de Mathématiques et de Sciences Physiques, Université d’Abomey-Calavi, Abomey-Calavi, Bénin. Diabetes is a chronic disease. In 2019, it was ...

Novel targeted treatments increase the need for prompt hypertrophic cardiomyopathy (HCM) detection. However, its low prevalence (0.5%) and resemblance to common diseases present challenges that may ...

Automated external defibrillators (AEDs) and implantable cardioverter defibrillators (ICDs) are used to treat life-threatening arrhythmias. AEDs and ICDs use shock advice algorithms to classify ECG ...

Timely diagnosis of structural heart disease improves patient outcomes, yet many remain underdiagnosed. While population screening with echocardiography is impractical, ECG-based prediction models can ...

An asymptomatic male patient with definite LQTS with a normal ECG and QTc who was flagged by the AI. Photo Credit: J. Martijn Bos and Michael Ackerman. A new artificial intelligence (AI) solution ...