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Deep Convolutional Neural Networks and Learning ECG Features for Screening Paroxysmal Atrial Fibrillation Patients
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A periodic split attractor reconstruction method facilitates cardiovascular signal diagnoses and obstructive sleep apnea syndrome monitoring
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Power grid fault diagnosis model based on the time series density distribution of warning information
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Unveiling the secrets of neural network scaling for ECG classification
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An intelligent computer-aided approach for atrial fibrillation and atrial flutter signals classification using modified bidirectional LSTM network
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ECG-STAR: Spatio-temporal attention residual networks for multi-label ECG abnormality classification
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Using artificial intelligence and deep learning to optimise the selection of adult congenital heart disease patients in S-ICD screening
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An effective feature extraction method based on GDS for atrial fibrillation detection
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Enabling Pipeline Damage Detection and Structural Health Monitoring: A Residual Network–Based Ultrasonic Guided Wave Approach
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Intraday prediction of Borsa Istanbul using convolutional neural networks and feature correlations
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An end-to-end atrial fibrillation detection by a novel residual-based temporal attention convolutional neural network with exponential nonlinearity loss
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Multi-label correlation guided feature fusion network for abnormal ECG diagnosis
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Clinician-artificial intelligence collaboration: A win-win solution for efficiency and reliability in atrial fibrillation diagnosis
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Soft errors in DNN accelerators: A comprehensive review
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Multi-head CNN–RNN for multi-time series anomaly detection: An industrial case study
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Deep learning for sensor-based activity recognition: A survey
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The impact of the soft errors in convolutional neural network on GPUs: Alexnet as case study
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Electrocardiogram based arrhythmia classification using wavelet transform with deep learning model
inferred← citeshttps://doi.org/10.1016/j.sciaf.2025.e02687openalex-snapshot
GAF-GradCAM: Guided dynamic weighted fusion of temporal and frequency GAF 2D matrices for ECG-based arrhythmia detection using deep learning
inferred← citeshttps://doi.org/10.1016/j.smhl.2018.07.022openalex-snapshot
ECG-based driver inattention identification during naturalistic driving using Mel-frequency cepstrum 2-D transform and convolutional neural networks
inferred← citeshttps://doi.org/10.1016/j.sysarc.2025.103587openalex-snapshot
Toward TinyDPFL systems for real-time cardiac healthcare: Trends, challenges, and system-level perspectives on AI algorithms, hardware, and edge intelligence
inferred← citeshttps://doi.org/10.1016/j.visinf.2022.05.001openalex-snapshot
VisuaLizations As Intermediate Representations (VLAIR): An approach for applying deep learning-based computer vision to non-image-based data
inferred← citeshttps://doi.org/10.1021/acsami.0c12440openalex-snapshot
Substrate-Free Multilayer Graphene Electronic Skin for Intelligent Diagnosis
inferred← citeshttps://doi.org/10.1038/s41467-025-59482-yopenalex-snapshot
Atrial fibrillation detection via contactless radio monitoring and knowledge transfer
inferred← citeshttps://doi.org/10.1038/s41591-018-0268-3openalex-snapshot
Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network
inferred← citeshttps://doi.org/10.1038/s41598-019-56927-5openalex-snapshot
Precision Medicine and Artificial Intelligence: A Pilot Study on Deep Learning for Hypoglycemic Events Detection based on ECG
inferred← citeshttps://doi.org/10.1038/s41598-021-02179-1openalex-snapshot
Analyzing artificial intelligence systems for the prediction of atrial fibrillation from sinus-rhythm ECGs including demographics and feature visualization
inferred← citeshttps://doi.org/10.1038/s41598-021-94363-6openalex-snapshot
Classification of ECG signals using multi-cumulants based evolutionary hybrid classifier
inferred← citeshttps://doi.org/10.1038/s41598-023-38541-8openalex-snapshot
Accurate detection of paroxysmal atrial fibrillation with certified-GAN and neural architecture search
inferred← citeshttps://doi.org/10.1038/s41598-025-85722-8openalex-snapshot
A noninvasive hyperkalemia monitoring system for dialysis patients based on a 1D-CNN model and single-lead ECG from wearable devices
inferred← citeshttps://doi.org/10.1038/s42256-024-00898-4openalex-snapshot
Sparse learned kernels for interpretable and efficient medical time series processing
inferred← citeshttps://doi.org/10.1049/iet-spr.2018.5103openalex-snapshot
Deep neural network based approach for ECG classification using hybrid differential features and active learning
inferred← citeshttps://doi.org/10.1055/s-0038-1667083openalex-snapshot
Deep Learning on 1-D Biosignals: a Taxonomy-based Survey
inferred← citeshttps://doi.org/10.1063/1.5121995openalex-snapshot
Synthesis of cardiac signals using a Copula-approach
inferred← citeshttps://doi.org/10.1063/10.0019678openalex-snapshot
Smart epidermal electrophysiological electrodes: Materials, structures, and algorithms
inferred← citeshttps://doi.org/10.1063/5.0069272openalex-snapshot
Convolutional neural networks predict the onset of paroxysmal atrial fibrillation: Theory and applications
inferred← citeshttps://doi.org/10.1063/5.0152818openalex-snapshot
Evaluating the legacy of steganography approaches
inferred← citeshttps://doi.org/10.1063/5.0212068openalex-snapshot
Detection of atrial fibrillation from pulse waves using convolution neural networks and recurrence-based plots
inferred← citeshttps://doi.org/10.1063/5.0217416openalex-snapshot
Recent advances in the tools and techniques for AI-aided diagnosis of atrial fibrillation
inferred← citeshttps://doi.org/10.1080/0952813x.2019.1620870openalex-snapshot
Prediction of stock movement using phase space reconstruction and extreme learning machines
inferred← citeshttps://doi.org/10.1088/1361-6579/ab3632openalex-snapshot
SleepNet: automated sleep analysis via dense convolutional neural network using physiological time series
inferred← citeshttps://doi.org/10.1088/1361-6579/ac010fopenalex-snapshot
A multiview feature fusion model for heartbeat classification
inferred← citeshttps://doi.org/10.1088/1361-6579/acfa61openalex-snapshot
Atrial fibrillation detection with signal decomposition and dilated residual neural network
inferred← citeshttps://doi.org/10.1093/ehjdh/ztad018openalex-snapshot
Automatic screening of patients with atrial fibrillation from 24-h Holter recording using deep learning
inferred← citeshttps://doi.org/10.1101/2021.08.25.21262591openalex-snapshot
Automated diagnosis of atrial fibrillation in 24-hour Holter recording based on deep learning:a study with randomized and real-world data validation
inferred← citeshttps://doi.org/10.1101/2024.01.03.573822openalex-snapshot
A Neural Network for High-Precise and Well-Interpretable Electrocardiogram Classification
inferred← citeshttps://doi.org/10.1109/access.2019.2912226openalex-snapshot
Deep Ensemble Detection of Congestive Heart Failure Using Short-Term RR Intervals
inferred← citeshttps://doi.org/10.1109/access.2019.2918792openalex-snapshot
A Novel Deep Arrhythmia-Diagnosis Network for Atrial Fibrillation Classification Using Electrocardiogram Signals
inferred← citeshttps://doi.org/10.1109/access.2019.2919485openalex-snapshot
Early and Remote Detection of Possible Heartbeat Problems With Convolutional Neural Networks and Multipart Interactive Training
inferred← citeshttps://doi.org/10.1109/access.2019.2933507openalex-snapshot
Robust Detection of Atrial Fibrillation Using Classification of a Linearly-Transformed Window of R-R Intervals Tachogram
inferred← citeshttps://doi.org/10.1109/access.2019.2934928openalex-snapshot
Biosignal Generation and Latent Variable Analysis With Recurrent Generative Adversarial Networks
inferred← citeshttps://doi.org/10.1109/access.2019.2943197openalex-snapshot
Dual-Input Neural Network Integrating Feature Extraction and Deep Learning for Coronary Artery Disease Detection Using Electrocardiogram and Phonocardiogram
inferred← citeshttps://doi.org/10.1109/access.2019.2954708openalex-snapshot
Analysis of Varicose Veins of Lower Extremities Based on Vascular Endothelial Cell Inflammation Images and Multi-Scale Deep Learning
inferred← citeshttps://doi.org/10.1109/access.2019.2960116openalex-snapshot
Dense Convolutional Networks With Focal Loss and Image Generation for Electrocardiogram Classification
inferred← citeshttps://doi.org/10.1109/access.2020.2971576openalex-snapshot
Human Digital Twin for Fitness Management
inferred← citeshttps://doi.org/10.1109/access.2020.2986246openalex-snapshot
A Hybrid Network Based on Dense Connection and Weighted Feature Aggregation for Human Activity Recognition
inferred← citeshttps://doi.org/10.1109/access.2020.3006707openalex-snapshot
Interpretation of Electrocardiogram (ECG) Rhythm by Combined CNN and BiLSTM
inferred← citeshttps://doi.org/10.1109/access.2020.3012904openalex-snapshot
Detecting Noisy ECG QRS Complexes Using WaveletCNN Autoencoder and ConvLSTM
inferred← citeshttps://doi.org/10.1109/access.2020.3019734openalex-snapshot
A Method for Sleep Quality Analysis Based on CNN Ensemble With Implementation in a Portable Wireless Device
inferred← citeshttps://doi.org/10.1109/access.2020.3026968openalex-snapshot
Stages-Based ECG Signal Analysis From Traditional Signal Processing to Machine Learning Approaches: A Survey
inferred← citeshttps://doi.org/10.1109/access.2021.3049522openalex-snapshot
Fitness Monitoring System Based on Internet of Things and Big Data Analysis
inferred← citeshttps://doi.org/10.1109/access.2021.3064854openalex-snapshot
Semi-Supervised Recurrent Variational Autoencoder Approach for Visual Diagnosis of Atrial Fibrillation
inferred← citeshttps://doi.org/10.1109/access.2021.3097614openalex-snapshot
ECG Heartbeat Classification Using Multimodal Fusion
inferred← citeshttps://doi.org/10.1109/access.2021.3119630openalex-snapshot
Origins of ECG and Evolution of Automated DSP Techniques: A Review
inferred← citeshttps://doi.org/10.1109/access.2022.3158658openalex-snapshot
ECG-Based Driver’s Stress Detection Using Deep Transfer Learning and Fuzzy Logic Approaches
inferred← citeshttps://doi.org/10.1109/access.2023.3317793openalex-snapshot
Comparison of Supervised Learning Algorithms for Quality Assessment of Wearable Electrocardiograms With Paroxysmal Atrial Fibrillation
inferred← citeshttps://doi.org/10.1109/access.2023.3335176openalex-snapshot
Multimodal Neural Network for Recognition of Cardiac Arrhythmias Based on 12-Load Electrocardiogram Signals
inferred← citeshttps://doi.org/10.1109/access.2024.3467181openalex-snapshot
TransMixer-AF: Advanced Real-Time Detection of Atrial Fibrillation Utilizing Single-Lead Electrocardiogram Signals
inferred← citeshttps://doi.org/10.1109/access.2024.3524764openalex-snapshot
Combination Hand-Crafted Features and Semi-Supervised Features Selection From Deep Features for Atrial Fibrillation Detection
inferred← citeshttps://doi.org/10.1109/access65134.2025.11135571openalex-snapshot
A Novel Single-Stage Noise-Aware Deep Learning Approach for AF Detection on Edge Devices
inferred← citeshttps://doi.org/10.1109/bhi58575.2023.10313484openalex-snapshot
Towards Multi-Functional ECG Smart System Based on a Client-Edge-Cloud Architecture
inferred← citeshttps://doi.org/10.1109/bibm62325.2024.10822754openalex-snapshot
ECGMamba: Towards ECG Classification with State Space Models
inferred← citeshttps://doi.org/10.1109/cac57257.2022.10055397openalex-snapshot
A Novel Dilated Causal Convolutional and Transformer Attention Prototype Network with Cut Feature Map for ECG Classification
inferred← citeshttps://doi.org/10.1109/cpee50798.2020.9238743openalex-snapshot
Detection of Arrhythmia in Real-time using ECG Signal Analysis and Convolutional Neural Networks
inferred← citeshttps://doi.org/10.1109/csitss67709.2025.11294741openalex-snapshot
FPGA-Based Hardware Accelerator with RISC-V Processor for Real-Time CNN Inference on ECG Signals
inferred← citeshttps://doi.org/10.1109/cyberc58899.2023.00042openalex-snapshot
Multimodal Deep Learning for Enhanced Arrhythmia Detection Using ECG Time Series and Image Data
inferred← citeshttps://doi.org/10.1109/dasc/picom/datacom/cyberscitec.2018.00131openalex-snapshot
Time-Incremental Convolutional Neural Network for Arrhythmia Detection in Varied-Length Electrocardiogram
inferred← citeshttps://doi.org/10.1109/dsd.2018.00077openalex-snapshot
Inter-Patient ECG Classification Using Deep Convolutional Neural Networks
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