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

A Wide and Deep Transformer Neural Network for 12-Lead ECG Classification
Annamalai Natarajan, Yale Chang, Sara Mariani et al. Computing in cardiology, 2020. Cites: paper

Bag of Tricks for Electrocardiogram Classification with Deep Neural Networks
Seonwoo Min, Hyun-Soo Choi, Hyeongrok Han et al. Computing in cardiology, 2020. Cites: paper

Can Laplacian Eigenmaps be used for differentiation between healthy subjects and patients with corrected Tetralogy of Fallot?
Ben Jacobs, Amalia Villa Gómez, Jonathan Moeyersons et al. Computing in cardiology, 2020. Cites: paper

Cardiac Abnormality Detection in 12-lead ECGs with Deep Convolutional Neural Networks Using Data Augmentation
Lucas Weber, Maksym Gaiduk, Wilhelm Daniel Scherz et al. Computing in cardiology, 2020. Cites: paper

Cardiac Arrhythmias Identification by Parallel CNNs and ECG Time-Frequency Representation
Jonathan Roberto Torres Castillo, Karina Ríos, M. Castañeda. Computing in cardiology, 2020. Cites: paper

Cardiac Pathologies Detection and Classification in 12-lead ECG
Radovan Smíšek, Andrea Němcová, Lucie Maršánová et al. Computing in cardiology, 2020. Cites: paper

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

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

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