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

Granular Computing for Machine Learning: Pursuing New Development Horizons

Abstract: Undoubtedly, machine learning (ML) has demonstrated a wealth of far-reaching successes present both at the level of fundamental developments, design methodologies and numerous application ...
IEEE

Enhanced Signal Processing for Arrhythmia Detection in ECG: Comparing Various Machine Learning Approaches

Abstract: Electrocardiogram (ECG) signal classification is important for the early detection of cardiac arrhythmias and the avoidance of life-threatening complications. This work compares several ...
Frontiers

Eye-Tracking Biomarkers of Clinical Expertise in ECG Interpretation: Statistical and Machine Learning Evidence

Electrical and Computer Engineering Department, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia The final, formatted version of the article will be published soon. Interpreting ...