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Electrocardiogram (ECG) is an essential signal in monitoring human heart activities.
Physiobank, physiotoolkit, and physionet: components of a new research resource for complex physiologic signals
Ary L Goldberger, Luis AN Amaral, Leon Glass, Jeffrey M Hausdorff, Plamen Ch Ivanov, Roger G Mark, Joseph E Mietus, George B Moody, Chung-Kang Peng, and H Eugene Stanley · 2000
Earlier work this paper cites.
The apnea-ecg database
Thomas Penzel, George B Moody, Roger G Mark, Ary L Goldberger, and J Hermann Peter · 2000
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Ambulatory ecg and analysis of heart rate variability in parkinson’s disease
TH Haapaniemi, Ville Pursiainen, JT Korpelainen, HV Huikuri, KA Sotaniemi, and VV Myllylä · 2001
Earlier work this paper cites.
Deep inside convolutional networks: Visualising image classification models and saliency maps
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman · 2013
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Fragmented ecg as a risk marker in cardiovascular diseases
Rahul Jain, Robin Singh, Sundermurthy Yamini, and Mithilesh K Das · 2014
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A novel algorithm for the automatic detection of sleep apnea from single-lead ecg
Carolina Varon, Alexander Caicedo, Dries Testelmans, Bertien Buyse, and Sabine Van Huffel · 2015
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A review of ecg-based diagnosis support systems for obstructive sleep apnea
Oliver Faust, U Rajendra Acharya, EYK Ng, and Hamido Fujita · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Mimic-iii, a freely accessible critical care database
Alistair EW Johnson, Tom J Pollard, Lu Shen, Li-wei H Lehman, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony Celi, and Roger G Mark · 2016
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Comparing feature-based classifiers and convolutional neural networks to detect arrhythmia from short segments of ecg
Fernando Andreotti, Oliver Carr, Marco AF Pimentel, Adam Mahdi, and Maarten De Vos · 2017
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Af classification from a short single lead ecg recording: The physionet/computing in cardiology challenge 2017
Gari D Clifford, Chengyu Liu, Benjamin Moody, H Lehman Li-wei, Ikaro Silva, Qiao Li, AE Johnson, and Roger G Mark · 2017
Earlier work this paper cites.
Classification of ecg signals based on 1d convolution neural network
Dan Li, Jianxin Zhang, Qiang Zhang, and Xiaopeng Wei · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Robust ecg signal classification for detection of atrial fibrillation using a novel neural network
Zhaohan Xiong, Martin K Stiles, and Jichao Zhao · 2017
Earlier work this paper cites.
Convolutional recurrent neural networks for electrocardiogram classification
Martin Zihlmann, Dmytro Perekrestenko, and Michael Tschannen · 2017
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Cited alongside, same era.
A method to detect sleep apnea based on deep neural network and hidden markov model using single-lead ecg signal
Kunyang Li, Weifeng Pan, Yifan Li, Qing Jiang, and Guanzheng Liu · 2018
Cited alongside, same era.
Automated detection of obstructive sleep apnea events from a single-lead electrocardiogram using a convolutional neural network
Erdenebayar Urtnasan, Jong-Uk Park, Eun-Yeon Joo, and Kyoung-Joung Lee · 2018
Cited alongside, same era.
Ecg signal preprocessing and svm classifier-based abnormality detection in remote healthcare applications
A wide and deep transformer neural network for 12-lead ecg classification
Annamalai Natarajan, Yale Chang, Sara Mariani, Asif Rahman, Gregory Boverman, Shruti Vij, and Jonathan Rubin · 2020
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Self-supervised ecg representation learning for emotion recognition
Pritam Sarkar and Ali Etemad · 2020
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Ptb-xl, a large publicly available electrocardiography dataset
Patrick Wagner, Nils Strodthoff, Ralf-Dieter Bousseljot, Dieter Kreiseler, Fatima I Lunze, Wojciech Samek, and Tobias Schaeffter · 2020
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Ecg heartbeat classification based on resnet and bi-lstm
Yang Zhou, Haoxi Zhang, Yuan Li, and Guangjian Ning · 2020
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Classification of cardiac abnormalities from ecg signals using se-resnet
Zhaowei Zhu, Han Wang, Tingting Zhao, Yangming Guo, Zhuoyang Xu, Zhuo Liu, Siqi Liu, Xiang Lan, Xingzhi Sun, and Mengling Feng · 2020
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C Venkatesan, P Karthigaikumar, Anand Paul, S Satheeskumaran, and Rajagopal Kumar · 2018
Cited alongside, same era.
Classification of myocardial infarction with multi-lead ecg signals and deep cnn
Ulas Baran Baloglu, Muhammed Talo, Ozal Yildirim, Ru San Tan, and U Rajendra Acharya · 2019
Cited alongside, same era.
An effective lstm recurrent network to detect arrhythmia on imbalanced ecg dataset
Junli Gao, Hongpo Zhang, Peng Lu, and Zongmin Wang · 2019
Cited alongside, same era.
Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network
Awni Y Hannun, Pranav Rajpurkar, Masoumeh Haghpanahi, Geoffrey H Tison, Codie Bourn, Mintu P Turakhia, and Andrew Y Ng · 2019
Cited alongside, same era.
Lstm-based auto-encoder model for ecg arrhythmias classification
Borui Hou, Jianyong Yang, Pu Wang, and Ruqiang Yan · 2019
Cited alongside, same era.
Automated detection of shockable and non-shockable arrhythmia using novel wavelet-based ecg features
Manish Sharma, Swapnil Singh, Abhishek Kumar, Ru San Tan, and U Rajendra Acharya · 2019
Cited alongside, same era.
A novel approach osa detection using single-lead ecg scalogram based on deep neural network
Sinam Ajitkumar Singh and Swanirbhar Majumder · 2019
Cited alongside, same era.
Smartwatch performance for the detection and quantification of atrial fibrillation
Jeremiah Wasserlauf, Cindy You, Ruchi Patel, Alexander Valys, David Albert, and Rod Passman · 2019
Cited alongside, same era.
Constrained transformer network for ecg signal processing and arrhythmia classification
Chao Che, Peiliang Zhang, Min Zhu, Yue Qu, and Bo Jin · 2021
Later among the works it cites.
Ecg heartbeat classification based on an improved resnet-18 model
Enbiao Jing, Haiyang Zhang, ZhiGang Li, Yazhi Liu, Zhanlin Ji, and Ivan Ganchev · 2021
Later among the works it cites.
Clocs: Contrastive learning of cardiac signals across space, time, and patients
Dani Kiyasseh, Tingting Zhu, and David A Clifton · 2021
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Application of dense neural networks for detection of atrial fibrillation and ranking of augmented ecg feature set
Vessela Krasteva, Ivaylo Christov, Stefan Naydenov, Todor Stoyanov, and Irena Jekova · 2021
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Learning explainable time-morphology patterns for automatic arrhythmia classification from short single-lead ecgs
Hyeonjeong Lee and Miyoung Shin · 2021
Later among the works it cites.
Bat: Beat-aligned transformer for electrocardiogram classification
Xiaoyu Li, Chen Li, Yuhua Wei, Yuyao Sun, Jishang Wei, Xiang Li, and Buyue Qian · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
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Neurokit2: A python toolbox for neurophysiological signal processing
Dominique Makowski, Tam Pham, Zen J. Lau, Jan C. Brammer, François Lespinasse, Hung Pham, Christopher Schölzel, and S. H. Annabel Chen · 2021
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Sleep apnea detection based on multi-scale residual network
Hengyang Fang, Changhua Lu, Feng Hong, Weiwei Jiang, and Tao Wang · 2022
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