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

A Multi-Resolution Mutual Learning Network for Multi-Label ECG Classification
Huang Wei, Ning Wang, Panpan Feng et al. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2024. Cites: paper

CELL: Supplementing Context for Multi-modal Few-shot Cardiologist
Huaicheng Zhang, Jiguang Shi, Yue Ge et al. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2024. Cites: paper

DAMAL: Data Augmentation Aided Multi-channel Attention Fusion Network for Multi-label Myocardial Infarction Localization
Lin Guo, Qianyun Zhan, Nan Ma et al. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2024. Cites: paper

ECGMamba: Towards ECG Classification with State Space Models
Yupeng Qiang, Xunde Dong, Xiuling Liu et al. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2024. Cites: paper

Interpretable ECG analysis for myocardial infarction detection through counterfactuals
Toygar Tanyel, Sezgin Atmaca, Kaan Gökçe et al. Biomedical Signal Processing and Control, 2024. Cites: paper

Leveraging Convolutional Neural Network (CNN)-based Auto Encoders for Enhanced Anomaly Detection in High-Dimensional Datasets
M. Haseeb Javed, Madiha Anjum, Hassan A. Ahmed et al. Engineering Technology & Applied Science Research, 2024. Cites: dataset

Time-frequency transformation integrated with a lightweight convolutional neural network for detection of myocardial infarction
Kashvi Ankitbhai Sheth, Charvi Upreti, Manas Ranjan Prusty et al. BMC Medical Imaging, 2024. Cites: dataset, paper

Automated ECG Image Classification with InceptionV3
Antony Gitau, Victor Ruto, David YN Njoroge et al. Computing in cardiology, 2024. Cites: dataset, paper

DeepECG-SSL : Un modèle fondationnel d’ ECG exploitant l’apprentissage auto-supervisé pour améliorer la prédiction des maladies cardiovasculaires
Sowa Samo, Hugues Achille. 2024. Cites: paper

Evaluating the Quality of CycleGAN Generated ECG Data for Myocardial Infarction Classification
Sara Battiston, Roberto Sassi, Massimo Walter Rivolta. Computing in cardiology, 2024. Cites: dataset

Foundation model of ECG diagnosis: Diagnostics and explanations of any form and rhythm on ECG
Yuanyuan Tian, Zhiyuan Li, Yanrui Jin et al. Cell Reports Medicine, 2024. Cites: paper

On the Feasibility of Locating Myocardial Bridge Though the 12-Lead Electrocardiogram: A Case Study
MHD Jafar Mortada, Agnese Sbrollini, Peter Michael van Dam et al. Computing in cardiology, 2024. Cites: paper

Universal representations in cardiovascular ECG assessment: A self-supervised learning approach
Zhi‐Yong Liu, Ching‐Heng Lin, Yu-Chun Hsu et al. International Journal of Medical Informatics, 2024. Cites: paper

YOUR-Lead: YOLO and U-Net for Reconstruction of ECG Lead Signals
Rafael Silva, Yingyu Yang, Maëlis Morier et al. Computing in cardiology, 2024. Cites: dataset

An ECG-Based Model for Left Ventricular Hypertrophy Detection: A Machine Learning Approach
Marion Taconné, Valentina Corino, Luca Tommaso Mainardi. IEEE Open Journal of Engineering in Medicine and Biology, 2024. Cites: paper

Artificial intelligence–derived electrocardiographic aging and risk of atrial fibrillation: a multi-national study
Seunghoon Cho, Sujeong Eom, Daehoon Kim et al. European Heart Journal, 2024. Cites: paper

Synthetic ECG signals generation: A scoping review
Beatrice Zanchi, Giuliana Monachino, Luigi Fiorillo et al. Computers in Biology and Medicine, 2024. Cites: paper

Disentangled representational learning for anomaly detection in single-lead electrocardiogram signals using variational autoencoder
Maximilian Kapsecker, Matthias C. Möller, Stephan Jonas. Computers in Biology and Medicine, 2024. Cites: paper

Graph structure based data augmentation method
Kyung Geun Kim, Byeong Tak Lee. Biomedical Engineering Letters, 2024. Cites: paper

Um transformer hierárquico para classificação e diagnóstico de eletrocardiograma
Pedro Robles Dutenhefner, Tércia Maria Ribeiro Lima Rezende, Gisele Lobo Pappa et al. Journal of Health Informatics, 2024. Cites: paper

HuBERT-ECG as a self-supervised foundation model for broad and scalable cardiac applications
Edoardo Coppola, Mattia Savardi, Mauro Massussi et al. medRxiv, 2024. Cites: paper

A Domain Data-Driven Metric to Improve Traditional Visualization and Interaction with ECG Large Databases
Jean C. Polo, Juliana V. Castilla, Juan Camilo Torres et al. International Symposium on Medical Information Processing and Analysis (SIPAIM), 2024. Cites: paper

Combined Self-Supervised Learning for ECG Classification Based on the Classification Token
Doga Gündüzalp, Congyu Zou. IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI ...), 2024. Cites: paper

MACRO: A Multi-Head Attentional Convolutional Recurrent Network for the Classification of Co-Occurring Diseases in 12-Lead ECGs
Vanessa Borst, Robert Leppich, Samuel Kounev. IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI ...), 2024. Cites: paper

Electrocardiogram sampling frequency for the optimal performance of complexity analysis and machine learning models: Discrimination between patients with and without paroxysmal atrial fibrillation using sinus rhythm electrocardiograms
Steven Creasy, Vadim Alexeenko, Gregory Y.H. Lip et al. Heart Rhythm O2, 2024. Cites: dataset, paper

The Role of Machine Learning in the Detection of Cardiac Fibrosis in Electrocardiograms: Scoping Review
Julia Handra, Hannah James, Ashery Mbilinyi et al. JMIR Cardio, 2024. Cites: paper

Towards Reliable ECG Analysis: Addressing Validation Gaps in the Electrocardiographic R-Peak Detection
Syed Talha Abid Ali, Sebin Kim, Young‐Joon Kim. Applied Sciences, 2024. Cites: paper

Deep Learning for ECG Anomaly Detection: A Robust Real-Time Solution for Cancer Prediction
Bhavani Sankar Telaprolu. International Journal of Scientific Research in Computer Science Engineering and Information Technology, 2024. Cites: paper

Direct Lead Assignment: A Simple and Scalable Contrastive Learning Method for ECG and Its IoMT Applications
Wenhan Liu, Shurong Pan, Sheng Chang et al. IEEE Internet of Things Journal, 2024. Cites: paper

Machine learning approaches toward an understanding of acute kidney injury: current trends and future directions
Inyong Jeong, Namjun Cho, Se-Jin Ahn et al. The Korean Journal of Internal Medicine, 2024. Cites: paper

A Survey of Transformer Enabled Time Series Synthesis
Alexander Sommers, Logan Cummins, Sudip Mittal et al. IEEE International Conference on Collaboration and Internet Computing (CIC), 2024. Cites: paper

Cardiac Condition Classification Using 12-Lead ECG Recordings
Dorsa EPMoghaddam, Mehdi Razavi, Behnaam Aazhang. Asilomar Conference on Signals, Systems and Computers (ACSSC), 2024. Cites: paper

A Dual-path Interactive ECG Denoising Algorithm
Xiuxin Zhang, Meng Chen, Yongjian Li et al. International Congress on Image and Signal Processing (CISP), 2024. Cites: paper

A dual-branch convolutional neural network with domain-informed attention for arrhythmia classification of 12-lead electrocardiograms
Rucheng Jiang, Bin Fu, Renfa Li et al. Engineering Applications of Artificial Intelligence, 2024. Cites: paper

Solving the Inverse Problem of Electrocardiography for Cardiac Digital Twins: A Survey
Lei Li, Julià Camps, Blanca Rodríguez et al. IEEE Reviews in Biomedical Engineering, 2024. Cites: paper

A Fully-Automated Paper ECG Digitisation Algorithm for e-Health Applications
Tao Wang, Yiquan Wang, Zhisen Chang et al. International Conference on Wireless Communications and Signal Processing (WCSP), 2024. Cites: paper

An Embedded System for Real-Time Atrial Fibrillation Diagnosis Using a Multimodal Approach to ECG Data
Monalisa Akter, Nayeema Islam, Abdul Ahad et al. Eng—Advances in Engineering, 2024. Cites: paper

FedMAC: Tackling Partial-Modality Missing in Federated Learning with Cross-Modal Aggregation and Contrastive Regularization
Manh Duong Nguyen, Trung Thành Nguyễn, Huy‐Hieu Pham et al. IEEE International Symposium on Network Computing and Applications (NCA), 2024. Cites: paper

MoRE: Multi-Modal Contrastive Pre-training with Transformers on X-Rays, ECGs, and Diagnostic Report
Samrajya Thapa, Koushik Howlader, Bhattacharjee, Subhankar et al. arXiv (Cornell University), 2024. Cites: dataset

Empirical investigation of multi-source cross-validation in clinical ECG classification
Tuija Leinonen, David Wong, Antti Vasankari et al. Computers in Biology and Medicine, 2024. Cites: paper

ECG Monitoring System Based on Multi-Scale Convolutional Neural Network
Liyuan Zhang, Dmitry O. Budanov. International Conference on Electrical Engineering and Photonics (EExPolytech), 2024. Cites: paper

ECG Spectrogram and Modified InceptionNet for Cardiovascular Disease Classification
Việt Dũng Nguyễn, Thu-Thao Dao-Le. International Conference on Advanced Technologies for Communications, 2024. Cites: paper

Enhancing Explainability of Deep Learning-Based ECG Diagnosis Using Large Language Models
Shi Wu, Jianlong J. Zhou, Yifei Dong et al. International Conference on Advances in Artificial Intelligence (ICAAI), 2024. Cites: paper

Detection of Acute Myocardial Infarction Using Deep Learning on Lead-I ECG Data
Parmida Davarmanesh, Qian Lin, Irene Tenison et al. Wearable and Implantable Body Sensor Networks, 2024. Cites: paper

Heart Block Identification from 12-Lead ECG: Exploring the Generalizability of Self-Supervised AI
Teya S. Bergamaschi, Collin M. Stultz, Ridwan Alam. Wearable and Implantable Body Sensor Networks, 2024. Cites: paper

Split Without a Leak: Reducing Privacy Leakage in Split Learning
Khoa Nguyen, Tanveer Khan, Antonis Michalas. Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2024. Cites: paper

A Novel WTS-EDC Network for Multi-Source ECG Signal Classification
Ankur Rana, Vivek Kumar, Anish Gupta. Journal of The Institution of Engineers (India) Series B, 2024. Cites: paper

Variational Diffusion Posterior Sampling with Midpoint Guidance
Badr Moufad, Yazid Janati, Lisa Bedin et al. arXiv (Cornell University), 2024. Cites: paper

Bootstrap each lead’s latent: A novel method for self-supervised learning of multilead electrocardiograms
Wenhan Liu, Shurong Pan, Zhoutong Li et al. Computer Methods and Programs in Biomedicine, 2024. Cites: paper

Efficient CORDIC-Based Activation Functions for RNN Acceleration on FPGAs
Wan Shen, Junye Jiang, Minghan Li et al. IEEE Transactions on Artificial Intelligence, 2024. Cites: paper

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