A common misperception exists that electrocardiograms (ECGs) simply contain data about heart activity. However, modern ECGs enhanced with artificial intelligence (AI) can contain data about a ...
A machine-learning model based on Transformer architecture, a form of artificial intelligence originally developed for ...
Recognizing emotions objectively and accurately remains challenging because of the limited ecological validity, informational incompleteness, and constrained model performance of conventional ...
Background Despite standardised approaches, subjective assessment and inconsistent diagnostic testing for chest pain in the emergency department (ED) drive costs, disparities and adverse outcomes.
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 ...
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 ...
Mathematics is often seen by first-year engineering students as a theoretical subject disconnected from real-world applications. However, when we bring real-time relevance into the ...
Basic information and contact details for the University of Technology, Iraq The University of Technology, Iraq is one of Iraq’s largest universities and is located on the Eastern side of the city of ...
Early and accurate prediction of neurological outcomes in comatose patients following cardiac arrest is critical for informed clinical decision-making. Existing studies have predominantly focused on ...
aDepartment of Biomedical Engineering, Duke University, Durham, NC, USA bDepartment of Computer Science, Duke University, Durham, NC, USA cDepartment of Biostatistics & Bioinformatics, Duke University ...
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