Research graph
References from Generative recurrence analysis and metric learning for detection of atrial fibrillation from short ECG data. Local targets link to admitted publications; unresolved targets remain external evidence.
Atrial fibrillation
10.1038/nrdp.2016.16 · 2016 · External reference
Pattern recognition and automatic identification of early-stage atrial fibrillation
10.1016/j.eswa.2020.113560 · 2020 · External reference
Intrinsic recurrence quantification analysis of nonlinear and nonstationary short-term time series
10.1063/5.0006537 · 2020 · External reference
A national survey of the prevalence, incidence, primary care burden and treatment of atrial fibrillation in Scotland
10.1136/hrt.2006.107573 · 2007 · External reference
Epidemiology of atrial fibrillation in the 21st century
10.1161/circresaha.120.316340 · 2020 · External reference
Image-decomposition-enhanced deep learning for detection of rotor cores in cardiac fibrillation
10.1109/tbme.2023.3292383 · 2024 · External reference
Time series forecasting for nonlinear and non-stationary processes: A review and comparative study
10.1080/0740817x.2014.999180 · 2015 · External reference
Deep learning for ECG arrhythmia detection and classification: An overview of progress for period 2017–2023
10.3389/fphys.2023.1246746 · 2023 · External reference
Forecasting the evolution of nonlinear and nonstationary systems using recurrence-based local Gaussian process models
10.1103/physreve.82.056206 · 2010 · External reference
Gaussian mixture variational autoencoder with contrastive learning for multi-label classification
2022 · External reference
Fractal dynamics in physiology: Alterations with disease and aging
10.1073/pnas.012579499 · 2002 · External reference
Automated diagnosis of arrhythmia using combination of CNN and LSTM techniques with variable length heart beats
10.1016/j.compbiomed.2018.06.002 · 2018 · External reference
Prediction of paroxysmal atrial fibrillation using recurrence plot-based features of the RR-interval signal
10.1088/0967-3334/32/8/010 · 2011 · External reference
Predicting termination of atrial fibrillation based on the structure and quantification of the recurrence plot
10.1016/j.medengphy.2008.01.008 · 2008 · External reference
Dynamical assessment of physiological systems and states using recurrence plot strategies
10.1152/jappl.1994.76.2.965 · 1994 · External reference
Epileptic seizure prediction and control
10.1109/tbme.2003.810705 · 2003 · External reference
A review on the nonlinear dynamical system analysis of electrocardiogram signal
10.1155/2018/6920420 · 2018 · External reference
AF classification from a short single lead ECG recording: The PhysioNet/computing in cardiology challenge 2017
2017 · External reference
BioSPPy: A Python toolbox for physiological signal processing
10.1016/j.softx.2024.101712 · 2024 · External reference
A real-time QRS detection algorithm
10.1109/tbme.1985.325532 · 1985 · External reference
Temperature schedules for self-supervised contrastive methods on long-tail data
2022 · External reference
Comparing feature-based classifiers and convolutional neural networks to detect arrhythmia from short segments of ECG
2017 · External reference
Atrial fibrillation detection and ECG classification based on convolutional recurrent neural network
2017 · External reference
Deep multi-scale fusion neural network for multi-class arrhythmia detection
10.1109/jbhi.2020.2981526 · 2020 · External reference
Stacking segment-based CNN with SVM for recognition of atrial fibrillation from single-lead ECG recordings
10.1016/j.bspc.2021.102672 · 2021 · External reference
Automated identification of atrial fibrillation from single-lead ECGs using multi-branching ResNet
10.3389/fphys.2024.1362185 · 2024 · External reference
Heterogeneous recurrence analysis of heartbeat dynamics for the identification of sleep apnea events
10.1016/j.compbiomed.2016.05.006 · 2016 · External reference
Wireless wearable multisensory suite and real-time prediction of obstructive sleep apnea episodes
10.1109/jtehm.2013.2273354 · 2013 · External reference
