It is a common misperception that electrocardiograms (ECGs) simply contain data about heart activity. However, modern ECGs ...
At the University of California San Diego, researchers are asking what artificial intelligence can do for music — not just whether it can generate a song, but whether it can become a more responsive, ...
Recognizing emotions objectively and accurately remains challenging because of the limited ecological validity, informational incompleteness, and constrained model performance of conventional ...
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 ...
Bradyarrhythmia is a common and potentially serious cause of syncope, often difficult to detect due to its intermittent nature. Traditional ECG monitoring methods either provide low diagnostic ...
Version 1.0.0 consolidates the architecture, machine learning model, and multiplatform deployment strategy for educational and predictive use of ECG data. ECGTwinMentor simulates a digital twin of an ...
ECG-based machine learning offers a promising, interpretable approach for liver disease detection, particularly in resource-limited settings. By revealing clinically relevant biomarkers, this method ...
With the Sabarimala pilgrimage set to begin shortly, Cardiology at Doorstep (CAD) Foundation, floated by a group of health professionals in Mangaluru, donated two ECG machines to ‘Devotee Doctors of ...