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

Seeing Beyond the Image: ECG and Anatomical Knowledge-Guided Myocardial Scar Segmentation from Late Gadolinium-Enhanced Images
Farheen Ramzan, Yusuf Kiberu, Nikesh Jathanna et al. IEEE International Symposium on Biomedical Imaging (ISBI), 2026. Cites: paper

Wavelet-Domain Multi-Representation and Ensemble Learning for Automated ECG Analysis
Lina Chato, Alex Kagozi. IEEE International Symposium on Biomedical Imaging (ISBI), 2026. Cites: paper

MAF-Net: Multimodal cross-attention-based fusion network for cardiovascular disease classification
Chang Qu, Xin Zhang, Yansong Lu et al. PLoS ONE, 2026. Cites: paper

ECG Foundation Models and Medical LLMs for Agentic Cardiovascular Intelligence at the Edge: A Review and Outlook
Mudassir Hasan Khan, Ahmad Nayfeh, Mudassir Masood et al. arXiv (Cornell University), 2026. Cites: dataset

CURE: Privacy-Preserving Split Learning Done Right
Halil İbrahim Kanpak, Aqsa Shabbir, Esra Genç et al. Proceedings on Privacy Enhancing Technologies, 2026. Cites: paper

ECG Classification on PTB-XL: A Data-Centric Approach with Simplified CNN-VAE
Naqcho Ali Mehdi, Saad Qasim Khan, Arfan Ghani et al. International Conference on Electrical/Electronics, Robotics, Artificial Intelligence, and Informatics (ICERAI), 2026. Cites: paper

High‐Fidelity Atrial Fibrillation Electrocardiogram Signal Generation Based on Mamba‐WGAN‐GP
Xingyu Chen, Yonghong Xu, Xianyou Zeng et al. Concurrency and Computation Practice and Experience, 2026. Cites: paper

Mamba: Efficient State-Space Modeling for Short-Window Atrial Fibrillation Detection from 12-Lead ECG
Mecheri Metidji, Abdou El Karim Tahari, Dounya Kassimi. International Conference on Pattern Analysis and Intelligent Systems (PAIS), 2026. Cites: paper

Adversarial Deep Learning Framework for Multimodal Authentication Using ECG and Fingerprint Biometrics
Abdullah Alduhailan, Nazhatul Hafizah Kamarudin. International Conference on Smart Multidomain Integrated Learning Environments (ICSMILE), 2026. Cites: paper

New Cardiovascular Signal Processing and Feature Engineering Methods for Disease Detection Based on Machine Learning
Haider Abdulkarim, Hussein Khaleel, Shaimaa Hameed Abd et al. International Journal of Electrical and Electronics Research, 2026. Cites: paper

A review on multi-sensor data fusion for wearable health monitoring
Arlene John, Alex Pappachen James, Barry Cardiff et al. Information Fusion, 2026. Cites: paper

From Foundation ECG Models to NISQ Learners: Distilling ECGFounder into a VQC Student
Giovanni S. Franco, Felipe Rodrigues Perche Mahlow, Ellison Fernando Cardoso et al. arXiv (Cornell University), 2026. Cites: paper

ST-Align: A time series and text alignment framework for cross-subject multivariate time series classification
Zhenghuang Wu, Tao Zhang, Ke Li et al. Neural Networks, 2026. Cites: paper

Retraction Notice: Intelligent ECG Classification Based on Improved Swin Transformer Model
Bin Xu, Zongzhen Yue, Shoucheng Ji et al. EAI Endorsed Transactions on Pervasive Health and Technology, 2026. Cites: paper

Lightweight and interpretable edge intelligence AI with intrusion detection for trustworthy cardiac arrhythmia in medical IoT
Muhammad Imran Khalid, Altaf Hussain, Nasir Hussain et al. Scientific Reports, 2026. Cites: paper

Deformable Convolutions Improve Time Series Classification by Capturing Sparsed Patterns
José Gilberto Barbosa de Medeiros Júnior, André Guarnier de Mitri, Maxime Devanne et al. ACM Symposium on Applied Computing, 2026. Cites: dataset

HMT-KD: Lightweight deep learning model for ECG analysis using hierarchical multi-teacher knowledge distillation framework
Nasim Beigzadeh, Abdolhossein Fathi. Applied Soft Computing, 2026. Cites: paper

Transfer learning is the electrocardiogram reconstruction capstone
Ekenedirichukwu Nelson Obianom, Abdulmalik Koya, Fan Feng et al. Computers in Biology and Medicine, 2026. Cites: paper

Demographic-Aware Self-Supervised Anomaly Detection Pretraining for Equitable Rare Cardiac Diagnosis
Chaoqin Huang, Zi Zeng, Aofan Jiang et al. arXiv (Cornell University), 2026. Cites: paper

VitalDB Arrhythmia Database: An Anesthesiologist-Validated Large-scale Intraoperative Arrhythmia Dataset with Beat and Rhythm Labels
Da-In Eun, K SHIM, Hyunsoo Lee et al. Scientific Data, 2026. Cites: paper

Diff-TGEG: a novel diffusion model for text-guided electrocardiogram generation
Rongjia Wang, Yihai Fang, Jianhong Dou et al. International Conference on Algorithms, High Performance Computing and Artificial Intelligence (AHPCAI), 2026. Cites: paper

A lightweight and robust method for electrocardiogram anomaly detection and localization using multi-scale masked autoencoder
Ya Zhou, Yujie Yang, Jianhuang Gan et al. PLoS ONE, 2026. Cites: paper

Sample-Wise False-Positive Reduction in ECG P-, R-, and T-Peak Detection via Physiological Temporal Constraints and Lightweight Binary Classifiers
Yutaka Yoshida, Kiyoko Yokoyama. Signals, 2026. Cites: paper

Teaching multimodal LLMs to comprehend 12-lead electrocardiographic images
Ruoqi Liu, Yuelin Bai, Xiang Yue et al. npj Digital Medicine, 2026. Cites: paper

Discovering Interpretable Semantics from Radio Signals for Contactless Cardiac Monitoring
Jinbo Chen, Haoyu Wang, Guixin Xu et al. Advanced Science, 2026. Cites: paper

ECG-GTMD: A CVD diagnosis model based on graph-transformer with multi-domain fusion of spatiotemporal and band features
Lihan Xia, Yun Zhang, Chong Fu et al. Information Sciences, 2026. Cites: paper

Optimized ECG Based Detection of Heart Abnormalities Using Federated Machine Learning
Vedant Kesharia, Atharva Rajmane, Pranay Khandagle et al. IEEE International Conference for Convergence in Computing Technology (I3CTCON), 2026. Cites: paper

Communication-Efficient Multimodal Federated Learning: Joint Modality and Client Selection
Liangqi Yuan, Dong-Jun Han, Su Wang et al. IEEE Transactions on Mobile Computing, 2026. Cites: paper

Enhancing ECG Classification Generalization Through Unified Multi-Dataset Training
Minchan Kim, Miyoung Shin. Sensors, 2026. Cites: paper

Learning Transferable Sensor Models via Language-Informed Pretraining
Yuliang Chen, Arvind Pillai, Yu Yvonne Wu et al. arXiv (Cornell University), 2026. Cites: dataset

From Prototypes to Sparse ECG Explanations: SHAP-driven Counterfactuals for Multivariate Time-series Multi-class Classification
Maciej Mozolewski, Betül Bayrak, Kerstin Bach et al. Information Systems Frontiers, 2026. Cites: paper

Global attention and multi-scale fusion dynamic extraction network for 12-lead ECG classification
Xiangqian Liu, Shihua Li, Bo Wang et al. Multimedia Systems, 2026. Cites: paper

Robustness vs. Efficiency in ECG Classification: A Comparative Study of Deep Learning and Classical Machine Learning Architectures
Amit Kumar Auddy, Jagannibas Paul Choudhury. Research Square, 2026. Cites: dataset, paper

CARDxnosis: Anatomico-clinical knowledge-driven explainable network with multi-domain information fusion for ECG diagnosis and report generation
Tushar Talukder Showrav, Soyabul Islam Lincoln, Md.Kamrul Hasan. Neurocomputing, 2026. Cites: paper

Physical activity recognition based on electrocardiogram data only
Sina Montazeri, Waltenegus Dargie, Yunhe Feng et al. Smart Health, 2026. Cites: paper

Multimodal Medical Image Binding via Shared Text Embeddings
Yunhao Liu, Suyang Xi, Shiqi Liu et al. IEEE Winter Conference on Applications of Computer Vision, 2026. Cites: paper

An Attentive Hybrid Network for Myocardial Infarction Severity and Risk Assessment
Akriti Jaiswal, Samarendra Dandapat, Prabin Kumar Bora. IEEE Sensors Journal, 2026. Cites: paper

Artificial intelligence—derived electrocardiographic age gap as a predictor of mortality after coronary revascularization: prognostic value and short-term intra-patient variability
Louise Vander Heyde, Karl Dujardin, Wim Anné et al. European Heart Journal - Digital Health, 2026. Cites: dataset, paper

fmmpy : a Python module for frequency-modulated Möbius signal decomposition
Christian Canedo, Rocío Carratalá-Sáez, Cristina Rueda. Journal of Statistical Computation and Simulation, 2026. Cites: paper

Graph-Informed and FiLM-Enhanced Multimodal Fusion for Myocardial Infarction Prediction
Xiantong Xiang, Longxiao Gao, Yuansheng Liu et al. IEEE Journal of Biomedical and Health Informatics, 2026. Cites: paper

Mamba-Based Prototypical Contrastive Learning With Augmented Feature Separation for Common and Rare Arrhythmia Classification
F F Guo, Ying An, Jianxin Wang. IEEE Journal of Biomedical and Health Informatics, 2026. Cites: paper

Sparse Temporal AutoEncoder for ECG Anomaly Detection
Radia Daci, Abdelmalik Taleb Ahmed, Luigi Patrono et al. Sensors, 2026. Cites: paper

Toward robust automated cardiovascular arrhythmia detection using self-supervised learning and 1-dimensional vision transformers
Mitchell John Violini Chatterjee, A. D. C. Chan, Majid Komeili. Scientific Reports, 2026. Cites: paper

Towards seamless myocardial infarction and cardiac rhythm detection: a deep learning approach with automated paper—electrocardiogram digitisation
Ravina Pramod Rai, Praveen Ashok Kumar, Mullasari Ajit Sankaradas et al. Indian Journal of Thoracic and Cardiovascular Surgery, 2026. Cites: paper

BioFPT: Biosignal Feature Pyramid Transformer for Self-Supervised Representation Learning From ECG Signals
Haobo Meng, Caiyuan Zhang, Fangfang Jiang et al. IEEE Journal of Biomedical and Health Informatics, 2026. Cites: paper

Temporal trends in myocardial ischemia risk estimated from 12-lead electrocardiograms using deep learning in individuals with suspected cancer during health checkups
Ken Kurisu, Maiko Fujimori, Kohei Takeshita et al. Cardio-Oncology, 2026. Cites: paper

HeartCHilD: Predicting Pediatric Congenital Heart Disease with Ensemble Convolutional ECG Screening
Ruhan Gupta. International Conference on Bioinformatics and Computational Biology (ICBCB), 2026. Cites: paper

SynthECG: Python Framework and ECG Image Datasets for Digitization, Lead Detection, and Waveform Segmentation
Masoud Rahimi, Reza Karbasi, Abdol‐Hossein Vahabie. Journal of Medical Signals & Sensors, 2026. Cites: paper

Condition-fusion-and-hiding denoising diffusion model for electrocardiogram lead reconstruction
Xiaoyang Wei, Zhiyuan Li, Yuanyuan Tian et al. iScience, 2026. Cites: dataset, paper

Automated detection of Chagas disease from ECG signals using wavelet scattering transform and RUSBoost classifier
Shivnarayan Patidar. Physiological Measurement, 2026. Cites: paper

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