Publications citing AF Classification from a Short Single Lead ECG Recording: The PhysioNet/Computing in Cardiology Challenge 2017 v1.0.0

A Meta-Transfer Learning Approach to ECG Arrhythmia Detection
Wuxia Chen, Taposh Banerjee, Eugene B John. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2022. Cites: paper

A Novel Method for the Extraction of Fetal ECG Signals from Wearable Devices
Shayan Chowdhury, Martin Gerbert Frasch, Maristella Lucchini et al. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2022. Cites: paper

Investigation of the Evolution of Wavelet Higher-Order Dynamics in Atrial Fibrillation
Charilaos A. Zisou, Georgios K. Apostolidis, Leontios J. Hadjileontiadis. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2022. Cites: paper

Issues in the automated classification of multilead ecgs using heterogeneous labels and populations
Matthew A. Reyna, Nadi Sadr, Erick Andres Perez Alday et al. Physiological Measurement, 2022. Cites: paper

LTH-ECG: Lottery Ticket Hypothesis-based Deep Learning Model Compression for Atrial Fibrillation Detection from Single Lead ECG On Wearable and Implantable Devices
Ishan Sahu, Arijit Ukil, Sundeep Khandelwal et al. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2022. Cites: paper

Using Minimum Redundancy Maximum Relevance Algorithm to Select Minimal Sets of Heart Rate Variability Parameters for Atrial Fibrillation Detection
Szymon Buś, Konrad Jędrzejewski, Przemysław Guzik. Journal of Clinical Medicine, 2022. Cites: paper

A systematic review and Meta-data analysis on the applications of Deep Learning in Electrocardiogram
Musa Nehemiah, Abdulsalam Ya’u Gital, Nahla Aljojo et al. Journal of Ambient Intelligence and Humanized Computing, 2022. Cites: paper

Lead Separation and Combination: A Novel Unsupervised 12-Lead ECG Feature Learning Framework for Internet of Medical Things
Wenhan Liu, Qianxi Guo, Xinwei Gao et al. IEEE Internet of Things Journal, 2022. Cites: paper

State-of-the-Art Deep Learning Methods on Electrocardiogram Data: Systematic Review
Γεώργιος Πετμεζάς, Leandros Stefanopoulos, Vassilis Kilintzis et al. JMIR Medical Informatics, 2022. Cites: paper

CACHET-CADB: A Contextualized Ambulatory Electrocardiography Arrhythmia Dataset
Devender Kumar, Sadasivan K Puthusserypady, Helena Domínguez et al. Frontiers in Cardiovascular Medicine, 2022. Cites: paper

A clinical study on Atrial Fibrillation, Premature Ventricular Contraction, and Premature Atrial Contraction screening based on an ECG deep learning model
Jianyuan Hong, Hua‐Jung Li, Chung‐Chi Yang et al. Applied Soft Computing, 2022. Cites: paper

SCRIB: Set-Classifier with Class-Specific Risk Bounds for Blackbox Models
Zhen Lin, Lucas M. Glass, Michael Brandon Westover et al. Proceedings of the AAAI Conference on Artificial Intelligence, 2022. Cites: paper

Classification Of Ecg Signals Of Heart Beats Using Tf-Ts Lstm With Augmented Fuzzy Recurrence Eigenvalues
Tuan D. Pham. IEEE Image, Video, and Multidimensional Signal Processing Workshop (IVMSP), 2022. Cites: paper

Ensemble Learning-Based Atrial Fibrillation Detection From Single Lead ECG Wave for Wireless Body Sensor Network
Yu Liu, Junxin Chen, Bo Fang et al. IEEE Transactions on Network Science and Engineering, 2022. Cites: paper

Cepstral Analysis for Scoring the Quality of Electrocardiograms for Heart Rate Variability
Paolo Castiglioni, Gianfranco Parati, Andrea Faini. Frontiers in Physiology, 2022. Cites: paper

Exploring novel algorithms for atrial fibrillation detection by driving graduate level education in medical machine learning
Maurice Rohr, Christoph Reich, Andreas Höhl et al. Physiological Measurement, 2022. Cites: paper

Arrhythmia classification of 12-lead and reduced-lead electrocardiograms via recurrent networks, scattering, and phase harmonic correlation
Philip A. Warrick, Vincent Lostanlen, Michael Eickenberg et al. Physiological Measurement, 2022. Cites: paper

Gated Recurrent Unit-Based RNN for Remote Photoplethysmography Signal Segmentation
Rita Meziati Sabour, Yannick Benezeth. IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2022. Cites: paper

A ResNet based multiscale feature extraction for classifying multi-variate medical time series
Junke Zhu, Le Sun, Yilin Wang et al. KSII Transactions on Internet and Information Systems, 2022. Cites: paper

A Review of Automated Diagnosis of ECG Arrhythmia Using Deep Learning Methods
Praveen Kumar Tyagi, Neha Rathore, Deepak Parashar et al. Advances in bioinformatics and biomedical engineering book series, 2022. Cites: paper

Arrhythmia Classifier using Binarized Convolutional Neural Network for Resource-Constrained Devices
Ao Wang, Wenxing Xu, Hanshi Sun et al. International Conference on Communications, Information System and Computer Engineering (CISCE), 2022. Cites: paper

Auto-encoder and bidirectional long short-term memory based automated arrhythmia classification for ECG signal
M. Ramkumar, Rajat Kumar, A. Manjunathan et al. Biomedical Signal Processing and Control, 2022. Cites: paper

Benchmarking Deep Learning Methods for Arrhythmia Detection
Elena Merdjanovska, Aleksandra Rashkovska. International Convention on Information and Communication Technology, Electronics and Microelectronics, 2022. Cites: paper

Cardiac Arrhythmia Classification from 12-lead Electrocardiogram Using a Combination of Deep Learning Approaches
Marko Barišić, Alan Jović. International Convention on Information and Communication Technology, Electronics and Microelectronics, 2022. Cites: paper

The influence of atrial flutter in automated detection of atrial arrhythmias - are we ready to go into clinical practice?”
Viktor Domazetoski, Goran Gligorić, Milan M. Marinković et al. Computer Methods and Programs in Biomedicine, 2022. Cites: paper

Abnormality classification from electrocardiograms with various lead combinations
Zhuoyang Xu, Yangming Guo, Tingting Zhao et al. Physiological Measurement, 2022. Cites: paper

A Multimodel Fusion Method for Cardiovascular Disease Detection Using ECG
Guanghui Song, Jiajian Zhang, Dandan Mao et al. Emergency Medicine International, 2022. Cites: paper

A deep residual inception network with channel attention modules for multi-label cardiac abnormality detection from reduced-lead ECG
Apoorva Srivastava, Sawon Pratiher, Sazedul Alam et al. Physiological Measurement, 2022. Cites: paper

EKG-Diagnostik mithilfe künstlicher Intelligenz: aktueller Stand und zukünftige Perspektiven – Teil 1
Wilhelm Haverkamp, Nils Strodthoff, Carsten Walter Israel. Herzschrittmachertherapie + Elektrophysiologie, 2022. Cites: paper

Arrhythmia detection based on multi-scale fusion of hybrid deep models from single lead ECG recordings: A multicenter dataset study
Chenbin Ma, Ke Lan, Jing Wang et al. Biomedical Signal Processing and Control, 2022. Cites: paper

Edge2Analysis: A Novel AIoT Platform for Atrial Fibrillation Recognition and Detection
Jia‐Rong Chen, Yingfang Zheng, Yingshan Liang et al. IEEE Journal of Biomedical and Health Informatics, 2022. Cites: paper

A Dilated Residual Vision Transformer for Atrial Fibrillation Detection from Stacked Time-Frequency ECG Representations
Sawon Pratiher, Apoorva Srivastava, Yedla Bindu Priyatha et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2022. Cites: paper

Telemedicine in arrhythmology
Veronika Bulková, Jakub Pindor, Filip Plešinger et al. Vnitřní lékařství, 2022. Cites: paper

[A heart sound classification method based on complete ensemble empirical modal decomposition with adaptive noise permutation entropy and support vector machine].
Meijun Liu, Quanyu Wu, Sheng Ding et al. PubMed Central, 2022. Cites: paper

Golden Standard or Obsolete Method? Review of ECG Applications in Clinical and Experimental Context
Tibor Stračina, Marina Ronzhina, Richard Ředina et al. Frontiers in Physiology, 2022. Cites: paper

Identification of patients at risk of cardiac conduction diseases requiring a permanent pacemaker following TAVI procedure: a deep-learning approach on ECG signals
Marco Mamprin, Jo M. Zelis, Pim A.L. Tonino et al. International Conference on Biomedical Engineering and Technology (ICBET), 2022. Cites: paper

Early diagnosis and better rhythm management to improve outcomes in patients with atrial fibrillation: the 8th AFNET/EHRA consensus conference
Renate B. Schnabel, Elena Andreassi Marinelli, Elena Arbelo et al. EP Europace, 2022. Cites: paper

End-to-end sensor fusion and classification of atrial fibrillation using deep neural networks and smartphone mechanocardiography
Saeed Mehrang, Mojtaba Jafari Tadi, Timo Knuutila et al. Physiological Measurement, 2022. Cites: paper

Defending Against Adversarial Attack in ECG Classification With Adversarial Distillation Training
Jiahao Shao, Shijia Geng, Zhaoji Fu et al. Research Square, 2022. Cites: paper

State-of-the-art Deep Learning Methods on Electrocardiogram Data: A Systematic Review (Preprint)
Γεώργιος Πετμεζάς, Leandros Stefanopoulos, Vassiis Kilintzis et al. 2022. Cites: paper

Premature Beats Rejection Strategy on Paroxysmal Atrial Fibrillation Detection
Xiangyu Zhang, Jianqing Li, Zhipeng Cai et al. Frontiers in Physiology, 2022. Cites: paper

ECG Identity Recognition Based on Feature Reuse Residual Network
Zhengqiang Yang, Linyue Liu, Ning Li et al. Processes, 2022. Cites: paper

AFSense-ECG: Atrial Fibrillation Condition Sensing From Single Lead Electrocardiogram (ECG) Signals
Arijit Ukil, Leandro Marín, Subhas Chandra Mukhopadhyay et al. IEEE Sensors Journal, 2022. Cites: paper

Noise Cleaning of ECG on Edge Device Using Convolutional Sparse Contractive Autoencoder
Rohan Banerjee, Ayan Mukherjee, Avik Ghose. IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), 2022. Cites: paper

A contrastive learning approach for ICU false arrhythmia alarm reduction
Yuerong Zhou, Guoshuai Zhao, Jun Li et al. Scientific Reports, 2022. Cites: paper

Automatic classification of atrial fibrillation from short single-lead ECG recordings using a Hybrid Approach of Dual Support Vector Machine
Gamal G. N. Geweid, Jiande D. Z. Chen. Expert Systems with Applications, 2022. Cites: paper

Artificial intelligence and atrial fibrillation
Ojasav Sehrawat, Anthony H. Kashou, Peter A. Noseworthy. Journal of Cardiovascular Electrophysiology, 2022. Cites: paper

Atrial Fibrillation Detection Using Weight-Pruned, Log-Quantised Convolutional Neural Networks
Xiu Qi Chang, Ann Feng Chew, Benjamin Chen Ming Choong et al. IEEE Latin American Symposium on Circuits and Systems (LASCAS), 2022. Cites: paper

Unsupervised ECG Analysis: A Review
Kasra Nezamabadi, Neda Sardaripour, Benyamin Haghi et al. IEEE Reviews in Biomedical Engineering, 2022. Cites: paper

A Novel Heart Disease Classification Algorithm Based on Fourier Transform and Persistent Homology
Yin Ni, Fupeng Sun, Yihao Luo et al. IEEE International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA), 2022. Cites: paper

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