Arrhythmic heartbeat classification using 2d convolutional neural networks
Background Electrocardiogram (ECG) is a method of recording the electrical activity of the
heart and it provides a diagnostic means for heart-related diseases. Arrhythmia is any …
heart and it provides a diagnostic means for heart-related diseases. Arrhythmia is any …
A novel deep-learning-based framework for the classification of cardiac arrhythmia
Cardiovascular diseases (CVDs) are the primary cause of death. Every year, many people
die due to heart attacks. The electrocardiogram (ECG) signal plays a vital role in diagnosing …
die due to heart attacks. The electrocardiogram (ECG) signal plays a vital role in diagnosing …
[PDF][PDF] Enhancing Myoelectric Signal Classification Through Conditional Spectral Moments and Wavelet-Enhanced Time-Domain Descriptors
E Murugiah, HW Jino, IT Mariapushpam… - Traitement du …, 2024 - researchgate.net
This study underscores the imperative role of feature extraction and classification in the
domain of electromyography (EMG) signals. The efficacy of myoelectric pattern recognition …
domain of electromyography (EMG) signals. The efficacy of myoelectric pattern recognition …
Fundamentals, limitations, and the prospects of deep learning for biomedical image analysis
T Chandrakumar, DT Bennet, PS Bennet - 2023 - IET
The use of artificial intelligence (AI) in healthcare has made great strides in the past decade.
Several promising new applications are proving to be useful in medicine. The most …
Several promising new applications are proving to be useful in medicine. The most …
Evaluating Supervised Machine Learning Models for Zero-Day Phishing Attack Detection: A Comprehensive Study
Z Lotfi, S Valipourebrahimi, T Tran - 2023 - researchsquare.com
To have highly secure e-commerce websites, detecting and preventing cyber-attacks is of
high importance. Among diverse types of cyber-attacks, identifying zero-day attacks is …
high importance. Among diverse types of cyber-attacks, identifying zero-day attacks is …