Publications citing PTB-XL, a large publicly available electrocardiography dataset v1.0.3

Model for classification of heart failure severity in patients with hypertrophic cardiomyopathy using a deep neural network algorithm with a 12-lead electrocardiogram
Sanshiro Togo, Yuki Sugiura, Sayumi Suzuki et al. Open Heart, 2023. Cites: paper

Interpretability of Neural Networks applied to Electrocardiograms : Translational Applications in Cardiovascular Diseases
Ahmad Fall. theses.fr (ABES), 2023. Cites: paper

SIGxCL: A Signal–Image–Graph Cross-Modal Contrastive Learning Framework for CVD Diagnosis Based on Internet of Medical Things
Huaicheng Zhang, Wenhan Liu, Zhoutong Li et al. IEEE Internet of Things Journal, 2023. Cites: paper

Automatic Classification Normal ECGs Based on Normal PathECG and WaveECG Features
Elżbieta Pociask, Krzysztof Piotr Malinowski, MHD Jafar Mortada et al. Computing in cardiology, 2023. Cites: dataset

Generated ECG Signal Feasibility Evaluation for Classification
Gi-Won Yoon, Segyeong Joo. Computing in cardiology, 2023. Cites: paper

Influence of the Training Set Composition on the Estimation Performance of Linear ECG-Lead Transformations
Daniel Guldenring, Dewar Finlay, Raymond Bond et al. Computing in cardiology, 2023. Cites: paper

Spectral Cross-Domain Neural Network With Soft-Adaptive Threshold Spectral Enhancement
Che Liu, Sibo Lucas Cheng, Weiping Ding et al. IEEE Transactions on Neural Networks and Learning Systems, 2023. Cites: paper

AttentionCovidNet: Efficient ECG-based diagnosis of COVID-19
Wesley Chorney, Haifeng Wang, Lir‐Wan Fan. Computers in Biology and Medicine, 2023. Cites: paper

AI-Based Detection of Myocardial Infarction through Electrocardiogram Signals: A Review
Yasmine Shabaan, Naglaa Fathy, Tamer A. Mostafa et al. International Conference on Intelligent Computing and Information Systems (ICICIS), 2023. Cites: paper

PEACE: Private and Energy-Efficient Algorithm for Cardiac Evaluation on the EDGE using Modified Split Learning and Model Quantization
Ahmad Ayad, Mahdi Barhoush, Johnson Loh et al. International Conference on Information and Communication Systems (ICICS), 2023. Cites: paper

TT-DCWN: A Two-Task Branch Densely Connected Weight Network for Myocardial Infarction Detection and Location Using 12-Lead Raw Electrocardiograms
Yupeng Qiang, Xunde Dong, Yang Yang. China Automation Congress (CAC), 2023. Cites: paper

DAMS-Net: Dual attention and multi-scale information fusion network for 12-lead ECG classification
Rongzhou Zhou, Junfeng Yao, Qingqi Hong et al. Methods, 2023. Cites: paper

In-Distribution and Out-of-Distribution Self-Supervised ECG Representation Learning for Arrhythmia Detection
Sahar Soltanieh, Javad Hashemi, Ali Etemad. IEEE Journal of Biomedical and Health Informatics, 2023. Cites: paper

A More Secure Split: Enhancing the Security of Privacy-Preserving Split Learning
Tanveer Khan, Khoa Nguyen, Antonis Michalas. Lecture notes in computer science, 2023. Cites: paper

Exploring CNN and XAI-based Approaches for Accountable MI Detection in the Context of IoT-enabled Emergency Communication Systems
Helene Knof, Prachi Bagave, Michell Boerger et al. International Conference on the Internet of Things (IoT), 2023. Cites: paper

SRTNet: Scanning, Reading, and Thinking Network for myocardial infarction detection and localization
Kaige Liu, Tong Liu, Dunwei Wen et al. Expert Systems with Applications, 2023. Cites: paper

IoT System and Deep Learning Model to Predict Cardiovascular Disease Based on ECG Signal
Nizar Sakli, Chokri Baccouch, Hédia Bellali et al. Advances in Science Technology and Engineering Systems Journal, 2023. Cites: paper

A CNN based multifaceted signal processing framework for heart rate proctoring using Millimeter wave radar ballistocardiography
Rafid Umayer Murshed, Md. Abrar Istiak, Md. Toufiqur Rahman et al. Array, 2023. Cites: paper

ST-ReGE: A Novel Spatial-Temporal Residual Graph Convolutional Network for CVD
Huaicheng Zhang, Wenhan Liu, Sheng Chang et al. IEEE Journal of Biomedical and Health Informatics, 2023. Cites: paper

Explainable Deep Learning Based-System for Multilabel Classification of 12-Lead ECG
Yousra Chahinez Hadj Azzem, Fouzi Harrag. International Conference on Networking and Advanced Systems (ICNAS), 2023. Cites: paper

MSFNet: Multi-Stage Fusion Network for Myocardial Infarction Classification
Luming Zhang, Xuesong Su, Wenguang Zheng. International Conference on Computer Engineering and Intelligent Control (ICCEIC), 2023. Cites: paper

Applying Generative Models and Transfer Learning to Physiological Data Classification
José Fernando Núñez, Jamie Arjona, Adrián Tormos et al. Frontiers in artificial intelligence and applications, 2023. Cites: paper

IRIDIA-AF, a large paroxysmal atrial fibrillation long-term electrocardiogram monitoring database
Cédric Gilon, Jean-Marie Grégoire, Marianne Mathieu et al. Scientific Data, 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

Multi-scale SE-residual network with transformer encoder for myocardial infarction classification
Qingyu Yao, Luming Zhang, Wenguang Zheng et al. Applied Soft Computing, 2023. Cites: paper

ECG Synthesis via Diffusion-Based State Space Augmented Transformer
Md Haider Zama, Friedhelm Schwenker. Sensors, 2023. Cites: paper

A lightweight U-Net model for denoising and noise localization of ECG signals
Lei Hu, Wenjie Cai, Ziyang Chen et al. Biomedical Signal Processing and Control, 2023. Cites: paper

CardiAWARE: A Novel ECG-based Deep Neural Network Algorithm for Early Detection of Cardiac Conditions
Eashan Kosaraju. IEEE MIT Undergraduate Research Technology Conference (URTC), 2023. Cites: paper

Predictive maintenance of aircraft bleed air systems : an approach based on machine learning and variational autoencoders
William Todo. theses.fr (ABES), 2023. Cites: paper

Stochastic co-teaching for training neural networks with unknown levels of label noise
Bob D. de Vos, Gino E. Jansen, Ivana Išgum. Scientific Reports, 2023. Cites: paper

Artificial neural network–based modelling of pacemaker and its pace tracking using discrete wavelet transform–based finite dimension repetitive controller
Rijhi Dey, Rudra Sankar Dhar, Ujjwal Mondal. Transactions of the Institute of Measurement and Control, 2023. Cites: paper

Multi-center atrial fibrillation electrocardiogram (ECG) classification using Fourier space convolutional neural networks (FD-CNN) and transfer learning
Luiz Vasconcelos, Bryan O. Pérez Martínez, Madeline Kent et al. Journal of Electrocardiology, 2023. Cites: paper

ElectroCardioGuard: Preventing patient misidentification in electrocardiogram databases through neural networks
Michal Seják, Jakub Sido, David Žahour. Knowledge-Based Systems, 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

A token selection-based multi-scale dual-branch CNN-transformer network for 12-lead ECG signal classification
Siyuan Zhang, Cheng Lian, Bingrong Xu et al. Knowledge-Based Systems, 2023. Cites: paper

Classification of cardiac disorders using weighted visibility graph features from ECG signals
Gokhan Kutluana, İlker Türker. Biomedical Signal Processing and Control, 2023. Cites: paper

ECG-CL: A Comprehensive Electrocardiogram Interpretation Method Based on Continual Learning
Hongxiang Gao, Xingyao Wang, Zhenghua Chen et al. IEEE Journal of Biomedical and Health Informatics, 2023. Cites: paper

SwinDAE: Electrocardiogram Quality Assessment Using 1D Swin Transformer and Denoising AutoEncoder
Guanyu Chen, Tianyi Shi, Baoxing Xie et al. IEEE Journal of Biomedical and Health Informatics, 2023. Cites: paper

IM-ECG: An interpretable framework for arrhythmia detection using multi-lead ECG
Rui Tao, Lin Wang, Yingnan Xiong et al. Expert Systems with Applications, 2023. Cites: paper

Completing the Cabrera Circle: deriving adaptable leads from ECG limb leads by combining constraints with a correction factor
Henning Dathe, Dagmar Krefting, Nicolai Spicher. Physiological Measurement, 2023. Cites: paper

Electrocardiographic temporo-spatial assessment of depolarization and repolarization changes after epicardial arrhythmogenic substrate ablation in Brugada syndrome
Emanuela H. Locati, Peter Michael van Dam, Giuseppe Ciconte et al. European Heart Journal - Digital Health, 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

Deep Learning Techniques for ECG-based Disease Detection: A Structured Narrative Review
Faustine Faccin, El‐Hadi Djermoune, Pauline Guyot et al. HAL, 2023. Cites: dataset, paper

A resource-efficient ECG diagnosis model for mobile health devices
Rui Tao, Lin Wang, Binrong Wu. Information Sciences, 2023. Cites: paper

Comparative Study of Machine Learning Algorithms in Classifying HRV for the Driver’s Physiological Condition
Abdul Razak, Sharifah Noor Masidayu Sayed Ismail, Sumendra Yogarayan et al. Civil Engineering Journal, 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

Studying the Impact of Varying Sample Length of ECG Signal on Classification Accuracy
Hassan Raza Bukhari, Yongqiang Cheng, Qingde Li. International Conference on Automation and Computing (ICAC), 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

Using domain adaptation for classification of healthy and disease conditions from mobile-captured images of standard 12-lead electrocardiograms
Вадим Глинер, Vladimir V. Makarov, Arutyun Ishkhanovich Avetisyan et al. Scientific Reports, 2023. Cites: paper

Evaluation of uncertainty quantification methods in multi-label classification: A case study with automatic diagnosis of electrocardiogram
Marília Barandas, Lorenzo Famiglini, Andrea Campagner et al. Information Fusion, 2023. Cites: paper

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