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

Breaking Barriers in Stress Detection: An Inter-Subject Approach Using ECG Signals
Shahane Tigranyan, Arman Martirosyan. IEEE Annual International Computer Software and Applications Conference (COMPSAC), 2024. Cites: paper

Multi-expert ensemble ECG diagnostic algorithm using mutually exclusive–symbiotic correlation between 254 hierarchical multiple labels
Jiewei Lai, Yue Zhang, Chenyu Zhao et al. npj Cardiovascular Health, 2024. Cites: paper

Transferring Knowledge from 12-Lead to 1-Lead ECGs via Contrastive Learning
Sergey Skorik, Aram Avetisyan, Ekaterina Diatlinko et al. IEEE Annual International Computer Software and Applications Conference (COMPSAC), 2024. Cites: paper

A novel IMW-mrmr feature selection approach for early detection of hypertension with HRV analysis
A. R. Sohara Banu, V. Nagaveni. International Journal of Information Technology, 2024. Cites: dataset

Electrocardiogram signal classification for diagnosing heart abnormalities using a deep learning approach with lead-wise expert prior knowledge framework
Qiao Xiao. Universiti Putra Malaysia Institutional Repository (Universiti Putra Malaysia), 2024. Cites: paper

Large-area stretchable dynamic 18-lead ECG monitoring patch integrated with deep learning for cardiovascular disease diagnosis
Yidong Deng, Chengjun Wang, Tong Qiu et al. Cell Reports Physical Science, 2024. Cites: paper

A Contrastive Learning and Graph-based Approach for Missing Modalities in Multimodal Federated Learning
Thu Hang Phung, Binh Phu Nguyen, Thanh-Hung Nguyen et al. International Joint Conference on Neural Networks (IJCNN), 2024. Cites: paper

Improved Deep Learning Based ECG Classification through Automated Feature Selection and Weighted Loss Function
Timo De Waele, Daniel Peralta, Eli De Poorter et al. International Joint Conference on Neural Networks (IJCNN), 2024. Cites: paper

Multiscale Residual Network with Dynamic Depthwise Convolution for Multi-label 12-Lead ECG Classification
Linhai Xie, Yilei Man, Delong Shang. International Joint Conference on Neural Networks (IJCNN), 2024. Cites: paper

Enhancing ECG Heartbeat classification with feature fusion neural networks and dynamic minority-biased batch weighting loss function
Jiajun Cai, Junmei Song, Bo Peng. Physiological Measurement, 2024. Cites: paper

Scaling Representation Learning From Ubiquitous ECG With State-Space Models
Kleanthis Avramidis, Dominika Kunc, Bartosz Perz et al. IEEE Journal of Biomedical and Health Informatics, 2024. Cites: paper

Clinical knowledge-based ECG abnormalities detection using dual-view CNN-Transformer and external attention mechanism
Hui Li, Jiyang Han, Honghao Zhang et al. Computers in Biology and Medicine, 2024. Cites: paper

Deep learning based multimodal biomedical data fusion: An overview and comparative review
Junwei Duan, Jiaqi Xiong, Yinghui Li et al. Information Fusion, 2024. Cites: paper

Differentiated knowledge distillation: Patient-specific single-sample personalization for electrocardiogram diagnostic models
Xiaoyang Wei, Zhiyuan Li, Yuanyuan Tian et al. Engineering Applications of Artificial Intelligence, 2024. Cites: paper

Comprehensive ECG Signal Analysis for Heart Disease Classification: Integrating Neural Networks with Random Forest
Akshita Gour, Rajesh Wadhvani, Muktesh Gupta. International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2024. Cites: paper

A simplified model for predicting ventricular hypertrophy than traditional methods
Aditya Santra, Shuvangi Shaw, Tarak Das. International Journal of Science and Research Archive, 2024. Cites: paper

Towards explainability in artificial intelligence frameworks for heartcare: A comprehensive survey
M. U. Sreeja, Abin Oommen Philip, M. H. Supriya. Journal of King Saud University - Computer and Information Sciences, 2024. Cites: dataset

Detection of multiple cardiac abnormalities using Convolution, Positional Encoder and Transformer on 12-lead ECG recordings
Adam Ford, Jessica Lan, Kyle Kai Ho Ng. medRxiv, 2024. Cites: paper

PPG-ECG Conversion and Classification for Cardiac Activity Diagnosis
Mamoudou Sékou Diani, Mounir Boukadoum. IEEE Interregional NEWCAS Conference (NEWCAS), 2024. Cites: paper

ECG Signal Classification based on combined CNN Features and Optimised Support Vector Machine
Rafia Hassani, Mohamed Boumehraz, Maroua Hamzi. Electrotehnica Electronica Automatica, 2024. Cites: paper

Leadwise clustering multi-branch network for multi-label ECG classification
Feiyan Zhou, Lingzhi Chen. Medical Engineering & Physics, 2024. Cites: paper

MELEP: A Novel Predictive Measure of Transferability in Multi-label ECG Diagnosis
Cuong V. Nguyen, Hieu Minh Duong, Cuong Do. Journal of Healthcare Informatics Research, 2024. Cites: paper

The ECG Signal Monitoring System Using Machine Learning Methods and LoRa Technology
Sandra Śmigiel, Tomasz Topoliński, Damian Ledziński et al. Pomiary, Automatyka, Robotyka, 2024. Cites: paper

Deep learning based ECG segmentation for delineation of diverse arrhythmias
Chankyu Joung, Mijin Kim, Taejin Paik et al. PLoS ONE, 2024. Cites: paper

Uncertainty Calibrated Deep Regression for QT Interval Measurement in Reduced Lead Set ECGs
Peter Doggart, Alan Kennedy, Raymond Bond et al. Irish Signals and Systems Conference, 2024. Cites: paper

Honest-GE: 2-step heuristic optimization and node-level embedding empower spatial-temporal graph model for ECG
Huaicheng Zhang, Wenhan Liu, Deyu Luo et al. Information Sciences, 2024. Cites: paper

Exploring Interpretable AI Methods for ECG Data Classification
Jaya Ojha, Hårek Haugerud, Anis Yazidi et al. 2024. Cites: dataset

xECGArch: a trustworthy deep learning architecture for interpretable ECG analysis considering short-term and long-term features
Marc Goettling, Alexander Hammer, Hagen Malberg et al. Scientific Reports, 2024. Cites: dataset, paper

An adaptive threshold-based semi-supervised learning method for cardiovascular disease detection
Jiguang Shi, Zhoutong Li, Wenhan Liu et al. Information Sciences, 2024. Cites: paper

TSRNET: Simple Framework for Real-Time ECG Anomaly Detection with Multimodal Time and Spectrogram Restoration Network
Nhat-Tan Bui, Dinh-Hieu Hoang, Thinh Phan et al. IEEE International Symposium on Biomedical Imaging (ISBI), 2024. Cites: paper

Efficient electrocardiogram generation based on cardiac electric vector simulation model
Wenge Que, Yingnan Bian, Shengjie Chen et al. Computers in Biology and Medicine, 2024. Cites: paper

Towards Certifiable AI in Medicine: Illustrated for Multi-label ECG Classification Performance Metrics
Miriam Elia, Fabian Stieler, Fabian Ripke et al. IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS), 2024. Cites: paper

A Contrastive Learning Approach Based on ECG-Image
Chao Chen, Chao Che, Tianming Zhao. International Conference on Modeling, Natural Language Processing and Machine Learning (CMNM), 2024. Cites: paper

SSSD-ECG-nle: New Label Embeddings with Structured State-Space Models for ECG generation
Sergey Skorik, Aram Avetisyan. Ivannikov Memorial Workshop (IVMEM), 2024. Cites: paper

Inferring Electrocardiography From Optical Sensing Using Lightweight Neural Network
Yuenan Li, Xin Tian, Qiang Zhu et al. IEEE Transactions on Artificial Intelligence, 2024. Cites: paper

Shortcut learning in medical AI hinders generalization: method for estimating AI model generalization without external data
Cathy Ong Ly, Balagopal Unnikrishnan, Tony Tadic et al. npj Digital Medicine, 2024. Cites: paper

Prospects for artificial intelligence-enhanced electrocardiogram as a unified screening tool for cardiac and non-cardiac conditions: an explorative study in emergency care
Nils Strodthoff, Juan Miguel Lopez Alcaraz, Wilhelm Haverkamp. European Heart Journal - Digital Health, 2024. Cites: paper

Multi-label classification of arrhythmia using dynamic graph convolutional network based on encoder-decoder framework
Yuhao Cheng, Wenliang Zhu, Deyin Li et al. Biomedical Signal Processing and Control, 2024. Cites: paper

Predicting Cardiovascular Disease: A Scoping Survey on different Datasets and DL/ML Models using ECG
Nouhaila Akouz, Asmae El Ghazi, Wassima Moutaouakil et al. International Conference on Intelligent Systems and Computer Vision (ISCV), 2024. Cites: paper

Orbital learning: a novel, actively orchestrated decentralised learning for healthcare
Neeraj Kavan Chakshu, Perumal Nithiarasu. Scientific Reports, 2024. Cites: paper

Explaining deep learning for ECG analysis: Building blocks for auditing and knowledge discovery
Patrick Wagner, Temesgen Mehari, Wilhelm Haverkamp et al. Computers in Biology and Medicine, 2024. Cites: paper

ECG VisionSense: A Cloud-Deployed, Flask-Based Intelligent Cardiovascular Disease Diagnosis System
Vaibhav Pendke, Esha Gawate, Sejal Wasule et al. International Conference on Advancement in Computation & Computer Technologies (InCACCT), 2024. Cites: paper

PIF dataset: a comprehensive dataset of physiological and inertial features for recognition of human activities
Manpreet Kaur Dhaliwal, Rohini Sharma, Rajbinder Kaur. Multimedia Tools and Applications, 2024. Cites: paper

ECG-Image-Kit: a synthetic image generation toolbox to facilitate deep learning-based electrocardiogram digitization
Kshama Kodthalu Shivashankara, Deepanshi Deepanshi, Afagh Mehri Shervedani et al. Physiological Measurement, 2024. Cites: paper

MT-MV-KDF: A novel Multi-Task Multi-View Knowledge Distillation Framework for myocardial infarction detection and localization
Yupeng Qiang, Xunde Dong, Xiuling Liu et al. Biomedical Signal Processing and Control, 2024. Cites: paper

Nurses’ competency on electrocardiography interpretation in adult emergency room: Addis Ababa, Ethiopia, 2021. Multicenter cross-sectional study
Yegremew Haimanot Belay, Demmelash Gezahegn Nigatu, Birhanu Melaku et al. International Emergency Nursing, 2024. Cites: paper

Modelos de aprendizado profundo de baixo custo computacional para classificação de ritmo cardíaco.
Quenaz Bezerra Soares. Digital Library of Theses and Dissertations (Universidade de São Paulo), 2024. Cites: paper

Spatiotemporal 3-D Variations Modeling With Self-Attention for Multilabel ECG Classification
Pan Xia, Hao Zhang, Yicheng Yao et al. IEEE Sensors Journal, 2024. Cites: paper

A lightweight deep learning approach for detecting electrocardiographic lead misplacement
Yangcheng Huang, Mingjie Wang, Yi‐Gang Li et al. Physiological Measurement, 2024. Cites: paper

DS4U-Net: A Diffusion Model-Based Approach to Multi-Lead ECG Signal Generation
Tiantian Du, Jiwei Wang, Rui Qu et al. International Conference on Intelligent Computing and Signal Processing (ICSP), 2024. Cites: paper

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