[HTML][HTML] 1D convolutional neural networks and applications: A survey
During the last decade, Convolutional Neural Networks (CNNs) have become the de facto
standard for various Computer Vision and Machine Learning operations. CNNs are feed …
standard for various Computer Vision and Machine Learning operations. CNNs are feed …
A survey on ECG analysis
The electrocardiogram (ECG) signal basically corresponds to the electrical activity of the
heart. In the literature, the ECG signal has been analyzed and utilized for various purposes …
heart. In the literature, the ECG signal has been analyzed and utilized for various purposes …
Major advances in particle swarm optimization: theory, analysis, and application
EH Houssein, AG Gad, K Hussain… - Swarm and Evolutionary …, 2021 - Elsevier
Over the ages, nature has constantly been a rich source of inspiration for science, with much
still to discover about and learn from. Swarm Intelligence (SI), a major branch of artificial …
still to discover about and learn from. Swarm Intelligence (SI), a major branch of artificial …
Automatic ECG classification using continuous wavelet transform and convolutional neural network
Early detection of arrhythmia and effective treatment can prevent deaths caused by
cardiovascular disease (CVD). In clinical practice, the diagnosis is made by checking the …
cardiovascular disease (CVD). In clinical practice, the diagnosis is made by checking the …
LSTM-based ECG classification for continuous monitoring on personal wearable devices
S Saadatnejad, M Oveisi… - IEEE journal of biomedical …, 2019 - ieeexplore.ieee.org
Objective: A novel electrocardiogram (ECG) classification algorithm is proposed for
continuous cardiac monitoring on wearable devices with limited processing capacity …
continuous cardiac monitoring on wearable devices with limited processing capacity …
A deep learning approach for ECG-based heartbeat classification for arrhythmia detection
G Sannino, G De Pietro - Future Generation Computer Systems, 2018 - Elsevier
Classification is one of the most popular topics in healthcare and bioinformatics, especially
in relation to arrhythmia detection. Arrhythmias are irregularities in the rate or rhythm of the …
in relation to arrhythmia detection. Arrhythmias are irregularities in the rate or rhythm of the …
Real-time patient-specific ECG classification by 1-D convolutional neural networks
Goal: This paper presents a fast and accurate patient-specific electrocardiogram (ECG)
classification and monitoring system. Methods: An adaptive implementation of 1-D …
classification and monitoring system. Methods: An adaptive implementation of 1-D …
Deep learning approach for active classification of electrocardiogram signals
In this paper, we propose a novel approach based on deep learning for active classification
of electrocardiogram (ECG) signals. To this end, we learn a suitable feature representation …
of electrocardiogram (ECG) signals. To this end, we learn a suitable feature representation …
An efficient ECG arrhythmia classification method based on Manta ray foraging optimization
The Electrocardiogram (ECG) arrhythmia classification has become an interesting research
area for researchers and developers as it plays a vital role in early prevention and diagnosis …
area for researchers and developers as it plays a vital role in early prevention and diagnosis …
A novel application of deep learning for single-lead ECG classification
Detecting and classifying cardiac arrhythmias is critical to the diagnosis of patients with
cardiac abnormalities. In this paper, a novel approach based on deep learning methodology …
cardiac abnormalities. In this paper, a novel approach based on deep learning methodology …