Open Heart

AI-enhanced electrocardiography as a digital biomarker platform in cardiovascular medicine: clinical applications, validation gaps and future implementation pathways

Artificial intelligence applied to the ECG is expanding the clinical role of this widely available diagnostic tool beyond ...
TCTMD

AI-ECG Models Detect Structural Heart Disease, Identify At-Risk Patients

The tools may help address underdiagnosis in this area, though there is still room for improvement in screening performance.

AI/ML Innovations Inc. Announces Grant of U.S. Patent Expanding Protection for AI-Driven ECG Analysis

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, ...
IEEE

Sleep Stage Classification Using a Non-contact Capacitive ECG Mattress with Machine Learning Approaches: A Feasible Study

Abstract: Sleep stage classification is essential for diagnosing sleep disorders. However, the clinical reliance on polysomnography (PSG) faces significant challenges due to its high cost, ...
GitHub

ECG-DualNet: Atrial Fibrillation Classification in Electrocardiography using Deep Learning

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 ...
IEEE

ECG Measurement System for Vehicle Implementation and Heart Disease Classification Using Machine Learning

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 ...
ahajournals.org

Multinational Federated Learning Approach to Train ECG and Echocardiogram Models for Hypertrophic Cardiomyopathy Detection

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 ...
ahajournals.org

rECHOmmend: An ECG-Based Machine Learning Approach for Identifying Patients at Increased Risk of Undiagnosed Structural Heart Disease Detectable by Echocardiography

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 ...