Publications citing PTB-XL, a large publicly available electrocardiography dataset v1.0.1

Diffusion-based conditional ECG generation with structured state space models
Juan Miguel Lopez Alcaraz, Nils Strodthoff. Computers in Biology and Medicine, 2023. Cites: paper

An Efficient and Private ECG Classification System Using Split and Semi-Supervised Learning
Ahmad Ayad, Mahdi Barhoush, Marian Frei et al. IEEE Journal of Biomedical and Health Informatics, 2023. Cites: paper

A Systematic Survey of Data Augmentation of ECG Signals for AI Applications
Md Moklesur Rahman, Massimo Walter Rivolta, Fabio Badilini et al. Sensors, 2023. Cites: paper

Importance of Electrode Selection and Number in Reconstructing Standard Twelve Lead Electrocardiograms
Adam Butchy, Utkars Jain, Michael Leasure et al. Biomedicines, 2023. Cites: paper

Benchmarking the Impact of Noise on Deep Learning-Based Classification of Atrial Fibrillation in 12-Lead ECG
Theresa Bender, Philip Hempel, Ennio Idrobo-Ávila et al. Studies in health technology and informatics, 2023. Cites: paper

Post Hoc Sample Size Estimation for Deep Learning Architectures for ECG-Classification
Lucas Bickmann, Lucas Plagwitz, Julian Varghese. Studies in health technology and informatics, 2023. Cites: dataset, paper

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

Cardiac Disease Diagnosis on Imbalanced Electrocardiography Data Through Optimal Transport Augmentation
Jielin Qiu, Jiacheng Zhu, Mengdi Xu et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2023. Cites: paper

Counterfactual Explanation for Multivariate Times Series Using A Contrastive Variational Autoencoder
William Todo, Merwann Selmani, Béatrice Laurent et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2023. Cites: paper

ECGT2T: Towards Synthesizing Twelve-Lead Electrocardiograms from Two Asynchronous Leads
Yong‐Yeon Jo, Young Sang Choi, Jong-Hwan Jang et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2023. Cites: paper

Text-to-ECG: 12-Lead Electrocardiogram Synthesis Conditioned on Clinical Text Reports
Hyunseung Chung, Jiho Kim, Joon‐myoung Kwon et al. IEEE International Conference on Acoustics Speech and Signal Processing, 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

CineECG analysis provides new insights into Familial ST-segment Depression Syndrome
Rasmus Frosted, Christian Paludan‐Müller, Oliver Bundgaard Vad et al. EP Europace, 2023. Cites: paper

Standardized Database of 12-Lead Electrocardiograms with a Common Standard for the Promotion of Cardiovascular Research: KURIAS-ECG
Hakje Yoo, Yunjin Yum, Soo Wan Park et al. Healthcare Informatics Research, 2023. Cites: paper

Normal and Abnormal ECG Signal Classification using Deep Learning
Renu Bahuguna, Soumya Upadhyay, Aditi Aditi et al. International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES), 2023. Cites: paper

Analysis of the Machine Learning Classification of Cardiac Disease on Embedded Systems
Sanda Thura, Jason B. Forsyth, Kevin Molloy et al. Systems and Information Engineering Design Symposium, 2023. Cites: paper

An organic electrochemical transistor for multi-modal sensing, memory and processing
Shijie Wang, Xi Chen, Chao Zhao et al. Nature Electronics, 2023. Cites: paper

Blockchain-enabled secure and efficient data sharing scheme for trust management in healthcare smartphone network
Rati Bhan, Rajendra Pamula, Parvez Faruki et al. The Journal of Supercomputing, 2023. Cites: paper

Left atrial overload detection in ECG using frequency domain features with machine learning and deep learning algorithms
Serkan Uslu, Nihal Öztürk, Selçuk Küçükseymen et al. Biomedical Signal Processing and Control, 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

Fusion of edge detection and graph neural networks to classifying electrocardiogram signals
Linh T. Duong, Doan Thi Hoai Thu, Cong Q. Chu et al. Expert Systems with Applications, 2023. Cites: paper

Deep Learning-Based ECG Arrhythmia Classification: A Systematic Review
Qiao Xiao, Khuan Lee, Siti Aisah Mokhtar et al. Applied Sciences, 2023. Cites: paper

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

Fourier space approach for convolutional neural network (CNN) electrocardiogram (ECG) classification: A proof-of-concept study
Madeline Kent, Luiz Vasconcelos, Sardar Ansari et al. Journal of Electrocardiology, 2023. Cites: paper

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

An ECG Classification Method Based on Multi-Task Learning and CoT Attention Mechanism
Quancheng Geng, Hui Liu, Tianlei Gao et al. Healthcare, 2023. Cites: dataset, paper

Artificial intelligence in clinical physiology: How to improve learning agility
D. V. Shutov, Daria E. Sharova, L. R. Abuladze et al. Digital Diagnostics, 2023. Cites: paper

Integrating multimodal information in machine learning for classifying acute myocardial infarction
Ran Xiao, Cheng Ding, Xiao Hu et al. Physiological Measurement, 2023. Cites: paper

An Attentive Spatio-Temporal Learning-Based Network for Cardiovascular Disease Diagnosis
Debasish Jyotishi, Samarendra Dandapat. IEEE Transactions on Systems Man and Cybernetics Systems, 2023. Cites: paper

Dense lead contrast for self-supervised representation learning of multilead electrocardiograms
Wenhan Liu, Zhoutong Li, Huaicheng Zhang et al. Information Sciences, 2023. Cites: paper

Heart disease classification based on ECG using machine learning models
Seyed Matin Malakouti. Biomedical Signal Processing and Control, 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

Hypergraph and cross-attention-based unsupervised domain adaptation framework for cross-domain myocardial infarction localization
Shuaiying Yuan, Ziyang He, Jianhui Zhao et al. Information Sciences, 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

Intelligent Electrocardiogram Analysis in Medicine: Data, Methods, and Applications
Yu-Xia Guan, Ying An, Feng-Yi Guo et al. Chinese Medical Sciences Journal, 2023. Cites: paper

Don't be fooled: label leakage in explanation methods and the importance of their quantitative evaluation
Neil Jethani, Adriel Saporta, Rajesh Ranganath. PubMed, 2023. Cites: paper

Pre-training in Medical Data: A Survey
Yixuan Qiu, Feng Lin, Weitong Chen et al. Machine Intelligence Research, 2023. Cites: paper

Bimodal CNN for cardiovascular disease classification by co-training ECG grayscale images and scalograms
Taeyoung Yoon, Daesung Kang. Scientific Reports, 2023. Cites: paper

Multi-Modal Stacking Ensemble for the Diagnosis of Cardiovascular Diseases
Taeyoung Yoon, Daesung Kang. Journal of Personalized Medicine, 2023. Cites: paper

A Deep Learning Architecture Using 3D Vectorcardiogram to Detect R-Peaks in ECG with Enhanced Precision
Maroua Mehri, Guillaume Calmon, Freddy Odille et al. Sensors, 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

Efficient Clustering-Based electrocardiographic biometric identification
David Meltzer, David Luengo. Expert Systems with Applications, 2023. Cites: paper

On Merging Feature Engineering and Deep Learning for Diagnosis, Risk Prediction and Age Estimation Based on the 12-Lead ECG
Eran Zvuloni, Jesse Read, Antônio H. Ribeiro et al. IEEE Transactions on Biomedical Engineering, 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 Multi-View Multi-Scale Neural Network for Multi-Label ECG Classification
Shunxiang Yang, Cheng Lian, Zhigang Zeng et al. IEEE Transactions on Emerging Topics in Computational Intelligence, 2023. Cites: paper

ECG Identification Based on the Gramian Angular Field and Tested with Individuals in Resting and Activity States
Carmen Cámara, Pedro Peris Lopez, Masoumeh Safkhani et al. Sensors, 2023. Cites: paper

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

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