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

Premature Ventricular Contraction Detection Based on Chebyshev Polynomials and K Nearest Neighbours Classifier
Fatima Guendouzi, Mokhtar Attari. Traitement du signal, 2023. Cites: paper

Automatic Classification Method of Arrhythmias Based on 12-Lead Electrocardiogram
Xiao Yu Yang, Zhong Ji. Sensors, 2023. Cites: paper

Self-Supervised Contrastive Learning for Medical Time Series: A Systematic Review
Ziyu Liu, Azadeh Alavi, Minyi Li et al. Sensors, 2023. Cites: paper

Interpretation of EKG with Image Recognition and Convolutional Neural Networks
Subrat Das, M. B. Epland, Yu Jiang et al. Current Problems in Cardiology, 2023. Cites: paper

Current and Future Use of Artificial Intelligence in Electrocardiography
Manuel Martínez‐Sellés, Manuel Marina Breysse. Journal of Cardiovascular Development and Disease, 2023. Cites: paper

Applications of Self-Supervised Learning to Biomedical Signals: where are we now
Federico Del Pup, Manfredo Atzori. 2023. Cites: paper

Novel HRV Metrics using Analytic Signal Representation of Interbeat Intervals for New Insights on Cardiac Dynamics
Sawon Pratiher, Apoorva Srivastava, Mrinal Acharya et al. 2023. Cites: paper

Classification of 27 heart abnormalities using 12-lead ECG signals with combined deep learning techniques
Atiaf Ayal Rawi, Murtada Khalafallah Elbashir, Awadallah M. Ahmed. Bulletin of Electrical Engineering and Informatics, 2023. Cites: paper

Evaluation of post-hoc interpretability methods in time-series classification
Hugues Turbé, Mina Bjelogrlic, Christian Lovis et al. Nature Machine Intelligence, 2023. Cites: paper

Detection of Fibrillatory Episodes in Atrial Fibrillation Rhythms via Topology-informed Machine Learning
Paul Samuel Ignacio. 2023. Cites: paper

Spatiotemporal self-supervised representation learning from multi-lead ECG signals
Rui Min Hu, Jie Chen, L. P. Zhou. Biomedical Signal Processing and Control, 2023. Cites: paper

Effective Delineation of ECG Signals for Operative Neural Disease Recognition and Classification
Aashim Dhawan. International Conference on Innovations in High Speed Communication and Signal Processing (IHCSP), 2023. Cites: paper

sCL-ST: Supervised Contrastive Learning With Semantic Transformations for Multiple Lead ECG Arrhythmia Classification
Duc Le, Sang Truong, Brijesh D. Patel et al. IEEE Journal of Biomedical and Health Informatics, 2023. Cites: paper

Atrial fibrillation classification based on the 2D representation of minimal subset ECG and a non-deep neural network
Hua Zhang, Chengyu Liu, Fangfang Tang et al. Frontiers in Physiology, 2023. Cites: paper

Algorithms for automated diagnosis of cardiovascular diseases based on ECG data: A comprehensive systematic review
Hanna Vitaliyivna Denysyuk, Rui João Pinto, Pedro Miguel Silva et al. Heliyon, 2023. Cites: paper

Deep learning approach to transformer-based arrhythmia classification using scalogram of single-lead ECG
Ji Seung Ryu, Solam Lee, Young Jun Park et al. Diagnostic and Therapeutic Applications of Light in Cardiology, 2023. Cites: paper

Development of Electrocardiogram Signal Generator for Fibrillation Detector
Ponco Siwindarto, Bill Jason, Adharul Muttaqin et al. Journal of Information Technology and Computer Science, 2023. Cites: paper

Using deep convolutional neural networks to predict patients age based on ECGs from an independent test cohort
Bjørn-Jostein Singstad, Belal Tavashi. Proceedings of the Northern Lights Deep Learning Workshop, 2023. Cites: paper

3D ECG display with deep learning approach for identification of cardiac abnormalities from a variable number of leads
Giovanni Bortolan. Physiological Measurement, 2023. Cites: paper

A novel temporal generative adversarial network for electrocardiography anomaly detection
Jing Qin, Fujie Gao, Zumin Wang et al. Artificial Intelligence in Medicine, 2023. Cites: paper

Improving generalization performance of electrocardiogram classification models
Hyeongrok Han, Seongjae Park, Seonwoo Min et al. Physiological Measurement, 2023. Cites: paper

AI and Machine Learning: The Basics
Nicolás Duchateau, Esther Puyol Anton, Bram Ruijsink et al. Springer eBooks, 2023. Cites: paper

Analysis of Non-imaging Data
Nicolás Duchateau, Óscar Cámara, Rafael Sebastián et al. Springer eBooks, 2023. Cites: paper

A Personal Health Agent for Decision Support in Arrhythmia Diagnosis
Tezira Wanyana, Mbithe Nzomo, Catherine Susan Price et al. Communications in computer and information science, 2023. Cites: paper

Applications of Self-Supervised Learning to Biomedical Signals: A Survey
Federico Del Pup, Manfredo Atzori. IEEE Access, 2023. Cites: paper

Diagnosis
Daniel Rueckert, Moritz A. Knolle, Nicolás Duchateau et al. Springer eBooks, 2023. Cites: paper

Entropy-based reliable non-invasive detection of coronary microvascular dysfunction using machine learning algorithm
Xiaoye Zhao, Yinlan Gong, Lihua Xu et al. Mathematical Biosciences & Engineering, 2023. Cites: paper

Joint Optimization of a $$\beta $$-VAE for ECG Task-Specific Feature Extraction
Viktor van der Valk, Douwe E. Atsma, Roderick W.C. Scherptong et al. Lecture notes in computer science, 2023. Cites: paper

Performance improvement of deep learning based multi-class ECG classification model using limited medical dataset
Sanghoon Choi, Hyo-Chang Seo, Min Soo Cho et al. IEEE Access, 2023. Cites: paper

ShapeWordNet: An Interpretable Shapelet Neural Network for Physiological Signal Classification
Wenqiang He, Mingyue Cheng, Qi Liu et al. Lecture notes in computer science, 2023. Cites: paper

Impact of Pre-Processing Decisions on Automated ECG Classification Accuracy
Adrian K. Cornely, Grace Mirsky. Computing in cardiology, 2022. Cites: paper

Interpretable Machine Learning Techniques in ECG-Based Heart Disease Classification: A Systematic Review
Yehualashet Megersa Ayano, Friedhelm Schwenker, Bisrat Derebssa Dufera et al. Diagnostics, 2022. Cites: paper

A joint cross-dimensional contrastive learning framework for 12-lead ECGs and its heterogeneous deployment on SoC
Wenhan Liu, Huaicheng Zhang, Sheng Chang et al. Computers in Biology and Medicine, 2022. Cites: paper

Application of Fourier-Bessel expansion and LSTM on multi-lead ECG for cardiac abnormalities identification
Nidhi Kalidas Sawant, Shivnarayan Patidar. Physiological Measurement, 2022. Cites: paper

A unique cardiac electrocardiographic 3D model. Toward interpretable AI diagnosis
Cristina Rueda, Alejandro Rodríguez-Collado, Itziar Fernández et al. iScience, 2022. Cites: paper

A novel multi-scale 2D CNN with weighted focal loss for arrhythmias detection on varying-dimensional ECGs
Pan Xia, Zhengling He, Zhongrui Bai et al. Physiological Measurement, 2022. Cites: paper

Ultra-low Power Analog Recurrent Neural Network Design Approximation for Wireless Health Monitoring
Yung-Ting Hsieh, Khizar Anjum, Dario Pompili. IEEE International Conference on Mobile Ad-Hoc and Sensor Systems (MASS), 2022. Cites: paper

Multimodality Multi-Lead ECG Arrhythmia Classification using Self-Supervised Learning
Thinh Phan, Duc Le, Brijesh D. Patel et al. IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI ...), 2022. Cites: paper

A novel deep learning package for electrocardiography research
Hao Wen, Jingsu Kang. Physiological Measurement, 2022. Cites: paper

A Priori Quantification of Transfer Learning Performance on Time Series Classification for Cyber-Physical Health Systems
Ryan Clark, Thomas E. Doyle. Conference proceedings - Canadian Conference on Electrical and Computer Engineering, 2022. Cites: paper

Ensemble classification combining ResNet and handcrafted features with three-steps training
Guadalupe García Isla, Federico Muscato, Andrea Sansonetti et al. Physiological Measurement, 2022. Cites: paper

Contrastive learning for atrial fibrillation detection in challenging scenarios
Karen Fonseca, Sergio Osorio, Jeyson Arley Castillo Bohórquez et al. European Signal Processing Conference (EUSIPCO), 2022. Cites: paper

Transfer learning enables prediction of myocardial injury from continuous single-lead electrocardiography
Boyang Tom Jin, Raj Palleti, Siyu Shi et al. Journal of the American Medical Informatics Association, 2022. Cites: paper

Label noise and self-learning label correction in cardiac abnormalities classification
Cristina Gallego Vázquez, Alexander Breuss, Oriella Gnarra et al. Physiological Measurement, 2022. Cites: paper

A Domain Generalization Approach for Out-Of-Distribution 12-lead ECG Classification with Convolutional Neural Networks
Aristotelis Ballas, Christos Diou. IEEE International Conference on Big Data Computing Service and Applications (BigDataService), 2022. Cites: paper

Cardiac Arrhythmia classification based on 3D recurrence plot analysis and deep learning
Hua Zhang, Chengyu Liu, Fangfang Tang et al. Frontiers in Physiology, 2022. Cites: paper

Multimodal 12-lead ECG data classification using multi-label DenseNet for heart disease detection
Xiao Juan Han, Enmei Tu, Jie Yang. International Conference on Data Science and Information Technology (DSIT), 2022. Cites: paper

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