Graph convolutional network‐based deep feature learning for cardiovascular disease recognition from heart sound signals
The high mortality rate and prevalence of cardiovascular disease (CVD) make early
detection of the disease essential. Due to its simplicity and low cost, the phonocardiogram …
detection of the disease essential. Due to its simplicity and low cost, the phonocardiogram …
Interpretability analysis of heartbeat classification based on heartbeat activity's global sequence features and BiLSTM-attention neural network
R Li, X Zhang, H Dai, B Zhou, Z Wang - IEEE Access, 2019 - ieeexplore.ieee.org
Arrhythmia is a disease that threatens human life. Therefore, timely diagnosis of arrhythmia
is of great significance in preventing heart disease and sudden cardiac death. The BiLSTM …
is of great significance in preventing heart disease and sudden cardiac death. The BiLSTM …
Machine learning for reliable network attack detection in SCADA systems
RL Perez, F Adamsky, R Soua… - 2018 17th IEEE …, 2018 - ieeexplore.ieee.org
Critical Infrastructures (CIs) use Supervisory Control And Data Acquisition (SCADA) systems
for remote control and monitoring. Sophisticated security measures are needed to address …
for remote control and monitoring. Sophisticated security measures are needed to address …
[HTML][HTML] Classifier identification using deep learning and machine learning algorithms for the detection of valvular heart diseases
Heart-related disorders are rapidly growing throughout the world. Artificial Intelligence with
computational methods plays a significant role in early detection and diagnosis. This study …
computational methods plays a significant role in early detection and diagnosis. This study …
[HTML][HTML] CNN-based classification of phonocardiograms using fractal techniques
Deep Learning based heart sound classification is of significant interest in reducing the
burden of manual auscultation through the automated detection of signals, including …
burden of manual auscultation through the automated detection of signals, including …
The implementation of pretrained AlexNet on PCG classification
Heart sounds are essential components of cardiac diagnosis, in which heart conditions can
be detected using phonocardiogram (PCG) signals. PCG signals provide useful information …
be detected using phonocardiogram (PCG) signals. PCG signals provide useful information …
Adversarial machine learning and speech emotion recognition: Utilizing generative adversarial networks for robustness
Deep learning has undoubtedly offered tremendous improvements in the performance of
state-of-the-art speech emotion recognition (SER) systems. However, recent research on …
state-of-the-art speech emotion recognition (SER) systems. However, recent research on …
Le-lwtnet: A learnable lifting wavelet convolutional neural network for heart sound abnormality detection
Automatic heart sound abnormality detection plays a vital role in the preliminary diagnosis of
cardiovascular diseases (CVDs). Many handcraft-designed or learning-based methods have …
cardiovascular diseases (CVDs). Many handcraft-designed or learning-based methods have …
Analysis of heart sound anomalies using ensemble learning
M Baydoun, L Safatly, H Ghaziri, A El Hajj - Biomedical Signal Processing …, 2020 - Elsevier
Phonocardiogram (PCG) signal analysis is a common method for evaluating the condition of
the heart and detecting possible anomalies such as cardiovascular diseases. This work …
the heart and detecting possible anomalies such as cardiovascular diseases. This work …
[HTML][HTML] The effect of signal duration on the classification of heart sounds: A deep learning approach
Deep learning techniques are the future trend for designing heart sound classification
methods, making conventional heart sound segmentation dispensable. However, despite …
methods, making conventional heart sound segmentation dispensable. However, despite …