Frontiers

End-to-End Non-Invasive ECG Signal Generation from PPG Signal: A Self-Supervised Learning Approach

The final, formatted version of the article will be published soon. Electrocardiogram (ECG) signals are frequently utilized for detecting important cardiac events, such as variations in ECG intervals, ...
Frontiers

Deep Learning-Based Early Prediction of Life-Threatening Ventricular Arrhythmias Using Long-Term Holter ECG Signals

1 Central People’s Hospital of Zhanjiang, Zhanjiang, China 2 Shenzhen Dawei Medical Technology Development Co., Ltd., Shenzhen, China, Shenzhen, China The final, formatted version of the article will ...
IEEE

Development and Validation of Feature-Based Machine Learning for ECG Artifact Detection and Classification

Abstract: ECG signals are vital for diagnosing cardiovascular diseases, but artifacts like power line interference, baseline wander, and motion artifacts hinder accurate interpretation. This study ...
IEEE

Enhancing Arrhythmia Diagnosis Through ECG Deep Learning Classification Deploying and Augmented Reality 3D Heart Visualization and Interaction

Abstract: Cardiovascular diseases (CVDs) continue to be a leading cause of mortality globally, highlighting the urgent need for timely and accurate diagnosis. Electrocardiography (ECG) is a vital ...
The Lancet

Machine learning prediction of 1-year mortality in older patients with heart failure: a nationwide, multicenter, prospective cohort study

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...