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, ...
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 ...
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 ...
Frontiers

Reinforcement Learning-Guided Optimization of ECG Features for Enhanced Heart Disease Prediction using Stacked CNNs

The final, formatted version of the article will be published soon. Accurate and timely heart disease diagnosis through intelligent ECG signal processing is essential to reducing death rates and ...
IEEE

Quantum Machine Learning: Recent Advances, Challenges, and Perspectives

Abstract: This study presents a comprehensive survey on Quantum Machine Learning (QML) along with its current status, challenges, and perspectives. QML combines quantum computing and machine learning ...