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

A System Detection of Atrial Fibrillation Using One ECG Derivation and Inductive Transfer Learning
Hermes J. Mora, Tomás Echaveguren, Esteban J. Pino. World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany, 2024. Cites: paper

Automatic Classification of Cardiac Arrhythmias Using Deep Learning Techniques: A Systematic Review
Fernando Vásquez-Iturralde, Marco Javier Flores-Calero, Felipe Grijalva et al. IEEE Access, 2024. Cites: paper

Detection of Heart Failure Using a Convolutional Neural Network (CNN) via ECG Signals
Medıkonda Ramya, T. Kishore Babu, Pathan. Hussain Basha et al. Information systems engineering and management, 2024. Cites: paper

DOST—Domain Obedient Self-supervision for Trustworthy Multi Label Classification with Noisy Labels
Soumadeep Saha, Utpal Garain, Arijit Ukil et al. Studies in computational intelligence, 2024. Cites: paper

ECG Based Heart Disease Classification: Advancement and Review of Techniques
Akshita Gour, Muktesh Gupta, Rajesh Wadhvani et al. Procedia Computer Science, 2024. Cites: paper

FedArtML: A Tool to Facilitate the Generation of Non-IID Datasets in a Controlled Way to Support Federated Learning Research
Daniel M. Jimenez-Gutierrez, Aris Anagnostopoulos, Ioannis Chatzigiannakis et al. IEEE Access, 2024. Cites: paper

Hunting Bunnies: Comparison of XAI methods for detection of right bundle branch blocks in 12-lead electrocardiograms
Jacqueline Michelle Metsch, Maurer Miriam Cindy, Philip Hempel et al. 2024. Cites: paper

Morphology-Aware ECG Diagnostic Framework With Cross-Task Attention Transfer for Improved Myocardial Infarction Diagnosis
Pharvesh Salman Choudhary, Samarendra Dandapat. IEEE Transactions on Instrumentation and Measurement, 2024. Cites: paper

Toward Robust Automated Cardiovascular Arrhythmia Detection using Self-supervised Learning and 1-Dimensional Vision Transformers
Mitchell John Violini Chatterjee. 2024. Cites: paper

Toward Trustworthiness of Deep Learning Models for 12-Lead ECGs
Theresa Bender. 2024. Cites: paper

Analyse avancée de signaux ECG acquis en IRM
Pierre Gabriel Aublin. 2023. Cites: paper

Semi-Supervised Learning for Multi-Label Cardiovascular Diseases Prediction: A Multi-Dataset Study
Rushuang Zhou, Lei Lü, Zijun Liu et al. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023. Cites: paper

Application of Federated Learning Techniques for Arrhythmia Classification Using 12-Lead ECG Signals
Daniel M. Jimenez-Gutierrez, Hafiz Muuhammad Hassan, Lorella Landi et al. Lecture notes in computer science, 2023. Cites: paper

Vector-Based Postprocessing Method for Improving ECG Denoising Techniques by Re-Establishing Lead Relationships
Amir Ghafari, Niusha Pourjafari, Ali Ghaffari. IEEE Transactions on Instrumentation and Measurement, 2023. Cites: paper

Dense neural network based arrhythmia classification on low-cost and low-compute micro-controller
Md Abu Obaida Zishan, H.M. Shihab, Sabik Sadman Islam et al. Expert Systems with Applications, 2023. Cites: paper

Stream Processing Architectures for Continuous ECG Monitoring Using Subsampling- Based Classifiers
Johnson Loh, Tobias Gemmeke. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2023. Cites: paper

Optimization of Using Multiple Machine Learning Approaches in Atrial Fibrillation Detection Based on a Large-Scale Data Set of 12-Lead Electrocardiograms: Cross-Sectional Study
Beau Bo-Sheng Chuang, Albert C. Yang. JMIR Formative Research, 2023. Cites: paper

Estimating age and gender from electrocardiogram signals: A comprehensive review of the past decade
Mohammed Yusuf Ansari, Marwa Qaraqe, Fatmeh Charafeddine et al. Artificial Intelligence in Medicine, 2023. Cites: paper

Unsupervised Pre-Training Using Masked Autoencoders for ECG Analysis
Guoxin Wang, Qingyuan Wang, Ganesh Neelakanta Iyer et al. IEEE Biomedical Circuits and Systems Conference (BioCAS), 2023. Cites: paper

Joint spatio-temporal features constrained self-supervised electrocardiogram representation learning
Ao Ran, Huafeng Liu. Biomedical Engineering Letters, 2023. Cites: paper

Selective Lead Integration: Enhancing ECG Classification for Effective Cardiac Monitoring
Ahmad Mousa, Khalid Elgazzar. IEEE World Forum on Internet of Things (WF-IoT), 2023. Cites: paper

Predictive maintenance of aircraft bleed air systems : an approach based on machine learning and variational autoencoders
William Todo. 2023. Cites: paper

Data programming enabled weak supervised labeling for ECG time series
Priyanka Gupta, Saandra Nandakumar, Manik Gupta et al. Biomedical Signal Processing and Control, 2023. Cites: paper

Early Detection of Coronary Microvascular Dysfunction Using Machine Learning Algorithm Based on Vectorcardiography and Cardiodynamicsgram Features
Xiaoye Zhao, Yinglan Gong, Jucheng Zhang et al. IRBM, 2023. Cites: paper

MVKT-ECG: Efficient single-lead ECG classification for multi-label arrhythmia by multi-view knowledge transferring
Yuzhen Qin, Li Sun, Hui Chen et al. Computers in Biology and Medicine, 2023. Cites: paper

MLCM: Multi-Label Confusion Matrix
Mohammadreza Heydarian, Thomas E. Doyle, Reza Samavi. 2023. Cites: paper

Augmentation Strategies for Self-Supervised Representation Learning from Electrocardiograms
Matilda Andersson, Mattias Nilsson, Gabrielle Flood et al. European Signal Processing Conference (EUSIPCO), 2023. Cites: paper

Efficient ECG-Based Atrial Fibrillation Detection via Parameterised Hypercomplex Neural Networks
Leonie Basso, Zhao Xu Ren, Wolfgang Nejdl. European Signal Processing Conference (EUSIPCO), 2023. Cites: paper

LIFEDATA - A Framework for Traceable Active Learning Projects
Fabian Stieler, Miriam Elia, Benjamin Weigell et al. IEEE International Requirements Engineering Conference Workshops (REW), 2023. Cites: paper

Towards Quantitative Precision for ECG Analysis: Leveraging State Space Models, Self-Supervision and Patient Metadata
Temesgen Mehari, Nils Strodthoff. IEEE Journal of Biomedical and Health Informatics, 2023. Cites: paper

Design and Implementation of an Atrial Fibrillation Detection Algorithm on the ARM Cortex-M4 Microcontroller
Marek Żyliński, Amir Nassibi, Danilo P. Mandic. Sensors, 2023. Cites: paper

Design and technical validation to generate a synthetic 12-lead electrocardiogram dataset to promote artificial intelligence research
Hakje Yoo, Jose Moon, Jong-Ho Kim et al. Health Information Science and Systems, 2023. Cites: paper

Towards Domain Generalization for ECG and EEG Classification: Algorithms and Benchmarks
Aristotelis Ballas, Christos Diou. IEEE Transactions on Emerging Topics in Computational Intelligence, 2023. Cites: paper

Introduction and Comparison of Novel Decentral Learning Schemes with Multiple Data Pools for Privacy-Preserving ECG Classification
Martin Baumgartner, Sai Pavan Kumar Veeranki, Dieter Hayn et al. Journal of Healthcare Informatics Research, 2023. Cites: paper

Predicting Age and Sex from Reduced Lead Electrocardiograms using Deep Learning
Felipe Meneguitti Dias, Estela Ribeiro, Quenaz Bezerra Soares et al. 2023. Cites: paper

MedTric : A clinically applicable metric for evaluation of multi-label computational diagnostic systems
Soumadeep Saha, Utpal Garain, Arijit Ukil et al. PLoS ONE, 2023. Cites: paper

Cardiac Arrhythmias Classification Using Machine Learning and Single-Lead ECG
Muhammad Asif Nauman, Carson Failor, Wala Saadeh. IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), 2023. Cites: paper

Machine learning-based detection of cardiovascular disease using ECG signals: performance vs. complexity
Huy Pham, Konstantin Egorov, Alexey Kazakov et al. Frontiers in Cardiovascular Medicine, 2023. Cites: paper

Optimization of Arrhythmia-based ECG-lead Selection for Computer-interpreted Heart Rhythm Classification
Serhii Reznichenko, Shijie Zhou. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2023. Cites: paper

Exploring the Feasibilities of Applying Min-Max Threshold Analysis with Machine Learning Techniques for Categorization of X-Wave in ECG Signal
Saravanan Velusamy, M. Pallikonda Rajasekaran, Kottaimalai Ramaraj et al. International Conference on Edge Computing and Applications (ICECAA), 2023. Cites: paper

Accurate detection of paroxysmal atrial fibrillation with certified-GAN and neural architecture search
Mehdi Asadi, Fatemeh Poursalim, Mohammad Loni et al. Scientific Reports, 2023. Cites: paper

Generation of Synthetic ECG Signal Using Generative Adversarial Network With Transformers
Hanamanth S Kaleli, Vasudev Dehalwar. International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2023. Cites: paper

Desarrollo de nuevos marcadores y clasificadores de bajo coste computacional para identificar afecciones cardiacas en registros ECG
Santiago Jiménez Serrano. 2023. Cites: paper

An Efficient Deep Learning Approach for Arrhythmia Classification using 3D Temporal SVCG
Lorenzo Simone, Mauro Giuseppe Camporeale, Nunzia Lomonte et al. IEEE International Conference on Digital Health (ICDH), 2023. Cites: paper

Diagnosing Left Bundle Branch Block in 12-lead Electrocardiogram using Self-Attention Convolutional Neural Networks
Alireza Sadeghi, Alireza Rezaee, Farshid Hajati. medRxiv, 2023. Cites: paper

Practical intelligent diagnostic algorithm for wearable 12-lead ECG via self-supervised learning on large-scale dataset
Jiewei Lai, Huixin Tan, Jinliang Wang et al. Nature Communications, 2023. Cites: paper

Heart Rhythm Abnormal Signal Diagnosis Based on Neural Network Deep Learning
Wang Jiao, Wei Wei. IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS), 2023. Cites: paper

PTB-XL+, a comprehensive electrocardiographic feature dataset
Nils Strodthoff, Temesgen Mehari, Claudia Nagel et al. Scientific Data, 2023. Cites: paper

Analysis of a Deep Learning Model for 12-Lead ECG Classification Reveals Learned Features Similar to Diagnostic Criteria
Theresa Bender, Jacqueline Michelle Metsch, Dagmar Krefting et al. IEEE Journal of Biomedical and Health Informatics, 2023. Cites: paper

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