Publications citing Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.2

Classification of 12-lead ECG Signals With Adversarial Multi-Source Domain Generalization
Hosein Hasani, Adeleh Bitarafan, Mahdieh Soleymani. Computing in cardiology, 2020. Cites: paper

Classification of 12 Lead ECG Signal Using 1D-CNN With Class Dependent Threshold
Rohit Pardasani, Navchetan Awasthi. Computing in cardiology, 2020. Cites: paper

Classification of 12-lead ECGs: the PhysioNet/Computing in Cardiology Challenge 2020
Matthew A. Reyna, Erick Andres Perez Alday, Annie Gu et al. Computing in cardiology, 2020. Cites: paper

Classification of 12-lead ECGs using digital biomarkers and representation learning
David Assaraf, Jeremy B Levy, Janmajay Singh et al. Computing in cardiology, 2020. Cites: paper

Classification of 12-lead ECGs Using Gradient Boosting on Features Acquired With Domain-Specific and Domain-Agnostic Methods
Durmus Umutcan Uguz, Felix Berief, Steffen K. Leonhardt et al. Computing in cardiology, 2020. Cites: paper

Classification of 12-lead ECGs Using Intra-Heartbeat Discrete-time Fourier Transform and Inter-Heartbeat Attention
Ibrahim Hammoud, I. V. Ramakrishnan, Petar M. Djurić. Computing in cardiology, 2020. Cites: paper

Classification of 12-lead ECG With an Ensemble Machine Learning Approach
Matteo Bodini, Massimo Walter Rivolta, Roberto Sassi. Computing in cardiology, 2020. Cites: paper

Classification of 12-Lead Electrocardiograms Using Residual Neural Networks and Transfer Learning
Sardar Ansari, Christopher E. Gillies, Brandon C. Cummings et al. Computing in cardiology, 2020. Cites: paper

Classification of Cardiac Abnormalities From ECG Signals Using SE-ResNet
Zhaowei Zhu, Han Wang, Tingting Zhao et al. Computing in cardiology, 2020. Cites: paper

Combining Scatter Transform and Deep Neural Networks for Multilabel ECG Signal Classification
Maximilian P. Oppelt, Maximilian Riehl, Felix P. Kemeth et al. Computing in cardiology, 2020. Cites: paper

Convolutional Neural Network and Rule-Based Algorithms for Classifying 12-lead ECGs
Bjørn-Jostein Singstad, Christian Tronstad. Computing in cardiology, 2020. Cites: paper

Convolutional Recurrent Neural Network and LightGBM Ensemble Model for 12-lead ECG Classification
Charilaos A. Zisou, Andreas Sochopoulos, Konstantinos Kitsios. Computing in cardiology, 2020. Cites: paper

Deep Multi-Label Multi-Instance Classification on 12-Lead ECG
Yingjing Feng, Edward Joseph Vigmond. Computing in cardiology, 2020. Cites: paper

Detecting Cardiac Abnormalities from 12-lead ECG Signals Using Feature Extraction, Dimensionality Reduction, and Machine Learning Classification
Garrett Perkins, J. Chase McGlinn, Muhammad Rizwan et al. Computing in cardiology, 2020. Cites: paper

Detection of Cardiac Arrhythmias From Varied Length Multichannel Electrocardiogram Recordings Using Deep Convolutional Neural Networks
Marwen Sallem, Adnen Saadaoui, Amina Ghrissi et al. Computing in cardiology, 2020. Cites: paper

Diagnostic of Multiple Cardiac Disorders from 12-lead ECGs Using Graph Convolutional Network Based Multi-label Classification
Zheheng Jiang, Tiago Paggi de Almeida, Fernando Soares Schlindwein et al. Computing in cardiology, 2020. Cites: paper

ECG Abnormalities Recognition Using Convolutional Network With Global Skip Connections and Custom Loss Function
Tomáš Vičar, Jakub Hejč, Petra Novotná et al. Computing in cardiology, 2020. Cites: paper

ECG Arrhythmia Classification using Non-Linear Features and Convolutional Neural Networks
Sebastián Andrés Cajas, Pedro Astaiza, David Santiago Garcia Chicangana et al. Computing in cardiology, 2020. Cites: paper

ECG Classification With a Convolutional Recurrent Neural Network
Halla Sigurthorsdottir, Jérôme Van Zaen, Ricard Delgado-Gonzalo et al. Computing in cardiology, 2020. Cites: paper

ECG Morphological Decomposition for Automatic Rhythm Identification
Guadalupe García Isla, Rita Laureanti, Valentina Corino et al. Computing in cardiology, 2020. Cites: paper

ECG Segmentation using a Neural Network as the Basis for Detection of Cardiac Pathologies
Philipp Sodmann, Marcus Vollmer. Computing in cardiology, 2020. Cites: paper

Electrocardiogram Classification by Modified EfficientNet with Data Augmentation
Naoki Nonaka, Jun Seita. Computing in cardiology, 2020. Cites: paper

Explainable Deep Neural Network for Identifying Cardiac Abnormalities Using Class Activation Map
Yu‐Cheng Lin, Yun-Chieh Lee, Wen-Chiao Tsai et al. Computing in cardiology, 2020. Cites: paper

Identification of Cardiac Arrhythmias from 12-lead ECG using Beat-wise Analysis and a Combination of CNN and LSTM
Mohanad Alkhodari, Leontios J. Hadjileontiadis, Ahsan Habib Khandoker. Computing in cardiology, 2020. Cites: paper

Impact of Neural Architecture Design on Cardiac Abnormality Classification Using 12-lead ECG Signals
Najmeh Fayyazifar, Selam Ahderom, David Suter et al. Computing in cardiology, 2020. Cites: paper

Interpretable XGBoost Based Classification of 12-lead ECGs Applying Information Theory Measures From Neuroscience
Hardik Rajpal, Madalina I Sas, Rebecca Joakim et al. Computing in cardiology, 2020. Cites: paper

MADNN: A Multi-scale Attention Deep Neural Network for Arrythmia Classification
Ran Duan, Xiaodong He, Ouyang Zhuoran. Computing in cardiology, 2020. Cites: paper

Multi-Class Classification of Pathologies Found on Short ECG Signals
Georgi I. Nalbantov, Svetoslav Ivanov, Jeffrey van Prehn. Computing in cardiology, 2020. Cites: paper

Multilabel 12-Lead Electrocardiogram Classification Using Gradient Boosting Tree Ensemble
Alexander William Wong, Weijie Sun, Sunil V. Kalmady et al. Computing in cardiology, 2020. Cites: paper

Multi-label Arrhythmia Classification From 12-Lead Electrocardiograms
Po‐Ya Hsu, Po‐Han Hsu, Tsung‐Han Lee et al. Computing in cardiology, 2020. Cites: paper

Multi-Label Classification of 12-lead ECGs by Using Residual CNN and Class-Wise Attention
Yang Liu, Kuanquan Wang, Yongfeng Yuan et al. Computing in cardiology, 2020. Cites: paper

Multi-label Classification of Abnormalities in 12-Lead ECG Using Deep Learning
Ao Ran, Dongsheng Ruan, Zheng Yuan et al. Computing in cardiology, 2020. Cites: paper

Multi-label Classification of Electrocardiogram With Modified Residual Networks
Shan Yang, Heng Xiang, Qingda Kong et al. Computing in cardiology, 2020. Cites: paper

Multi-Stream Deep Neural Network for 12-Lead ECG Classification
Martin Baumgartner, Dieter Hayn, Andreas Ziegl et al. Computing in cardiology, 2020. Cites: paper

On the Application of Convolutional Neural Networks for 12-lead ECG Multi-label Classification using Datasets from Multiple Centers
Davide Borra, Alice Andalò, Stefano Severi et al. Computing in cardiology, 2020. Cites: paper

Rhythm classification of 12-lead ECGs using deep neural network and class-activation maps for improved explainability
Sebastian D. Goodfellow, Dmitrii Shubin, Danny Eytan et al. Computing in cardiology, 2020. Cites: paper

Rule-Based methods and Deep Learning Networks for Automatic Classification of ECG
Giovanni Bortolan, Ivaylo Ivanov Christov, Iana Ivaylova Simova. Computing in cardiology, 2020. Cites: paper

SE-ECGNet: Multi-scale SE-Net for Multi-lead ECG Data
Jiabo Chen, Tianlong Chen, Bin Xiao et al. Computing in cardiology, 2020. Cites: paper

Selected Features for Classification of 12-lead ECGs
Marek Żyliński, Gerard Cybulski. Computing in cardiology, 2020. Cites: paper

Utilization of Residual CNN-GRU with Attention Mechanism for Classification of 12-lead ECG
Petr Nejedlý, Adam Ivora, Ivo Viščor et al. Computing in cardiology, 2020. Cites: paper

Detecting Cardiac Abnormalities Using 12-Lead ECG and Deep Learning
Roneel V. Sharan. IEEE Recent Advances in Intelligent Computational Systems, 2020. Cites: paper

Electronic stethoscope for detecting heart abnormalities in athletes
Batyrkhan Sultanovich Omarov, Aidar Batyrbekov, Azizah Suliman et al. International Arab Conference on Information Technology (ACIT), 2020. Cites: paper

Towards assisted electrocardiogram interpretation using an AI-enabled Augmented Reality headset
P. Lampreave, Guillermo Jiménez-Pérez, I. Sanz et al. Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization, 2020. Cites: paper

Combining Scatter Transform and Deep Neural Networks for Multilabel Electrocardiogram Signal Classification
Maximilian P. Oppelt, Maximilian Riehl, Felix P. Kemeth et al. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft), 2020. Cites: paper

Deep Learning Algorithm Classifies Heartbeat Events Based on Electrocardiogram Signals
Yongbo Liang, Shimin Yin, Qunfeng Tang et al. Frontiers in Physiology, 2020. Cites: dataset

Quantification of Interpatient 12-lead ECG Variabilities within a Healthy Cohort
Claudia Nagel, Nicolas Pilia, Axel Loewe et al. Current Directions in Biomedical Engineering, 2020. Cites: paper

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