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

Adaptive ultra-lightweight 12-lead ECG reconstruction from limited leads via a vectorcardiogram-mediated cascade framework
Diao Limin, Hongyu Zhong, Yi Zheng et al. Biomedical Signal Processing and Control, 2026. Cites: paper

I-GraphECG: Observability-Based Lead Selection and Interpretable Disease Prediction from the 12-Lead ECG Using a Gray-Box Graph Electrophysiology Surrogate
Limin Zhao, Hongtao Xu, Pengjian Wang et al. Sensors, 2026. Cites: paper

CARDIA-X: Global Semantic Transition and Rough-Set Rules for Auditable Post Hoc Electrocardiographic Explainability
Pavlo Radiuk, Olexander Barmak, Liliana V. Klymenko et al. AI, 2026. Cites: paper

Hybrid Multi-Domain ECG Feature Learning with mRMR and CNN–Transformer for Cardiac Disease Classification
Mohammed Alnusayri, Sara Mumtaz, Bader Aldughayfiq et al. Bioengineering, 2026. Cites: paper

Why blinding sex is not enough: equitable discrimination, unequal operation in machine-learning detection of myocardial infarction from the ECG
Guilherme Cesar da Costa, Jose Gregorio Valero Rodriguez, Giulia fernandes de Oliveira da Costa et al. Journal of Electrocardiology, 2026. Cites: paper

Calibration and processing sensitivity of time-embedded three-dimensional electrocardiographic descriptors: a two-dataset benchmark
Alejandro Jesús Bermejo Valdés. medRxiv, 2026. Cites: dataset, paper

Uncertainty-quantified time–frequency neural operator (UQ-TF-NO) for discretization-invariant heart failure risk prediction from ECG signals
Victor Adeyi Odeh, Zhang XiaoLing, Clement Agaba et al. Applied Soft Computing, 2026. Cites: paper

A Novel Hybrid Transformer-Based Framework for Reconstruction-Based ECG Anomaly Detection
Aashish Sharma, Shweta Jain, Rishit Aggarwal et al. Lecture notes in networks and systems, 2026. Cites: paper

Label-efficient cross-population transfer learning for electrocardiographic risk stratification: evaluation across German, Chinese and US cohorts
Yan Wang, Yan Lu. Frontiers in Cardiovascular Medicine, 2026. Cites: paper

A deep learning framework for arrhythmia classification: mitigating data leakage and class imbalance in ECG analysis
Sudeshna Sani, Dipra Mitra, Pallab Banerjee et al. Journal of Medical Engineering & Technology, 2026. Cites: paper

AI-Enabled Atrial Fibrillation Detection, Prediction, and Classification Based on ECG Data: A Review
Kimia Tahvildari, Fatih Kahraman. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 2026. Cites: paper

Masked autoencoder with adaptive Time–Frequency Cross-Attention for ECG arrhythmia classification
Hailun Wang, Yuanhang Li, Jiaqi Deng et al. Biomedical Signal Processing and Control, 2026. Cites: paper

Comprehensive ECG Waveform Analysis for Machine Learning-Based Classification
Vidhi Sutaria, Arpit Jain. Lecture notes in networks and systems, 2026. Cites: paper

From Prediction to Confidence: A Survey of AI-Based ECG Uncertainty Quantification Methods
Ibrahima Sy, Ndeye Fatou Ngom, Cheikh H. T. C. Ndiaye. Lecture notes in networks and systems, 2026. Cites: paper

Accelerating Training of Neural Network ECG Arrhythmia Classification Using Segmentation Information
Lev L. Kalashnikov, Dmitry A. Rostov, Lev A. Smirnov. Scientific School Dynamics of Complex Networks and their Applications (DCNA), 2026. Cites: paper

Comparative Evaluation of Sliding Euclidean Pattern Quantisation Versus Center-Independent Local Binary Patterns for ECG-Based Detection of Left Ventricular Hypertrophy
Muatasim. M Abulmuttaleb Albakaa, Mohd Najeb Jamaludin. IEEE International Conference on Signal and Image Processing Applications (ICSIPA), 2026. Cites: paper

ESTI: Evolutionary Signal and Time-Series Inspection for Auditing ECG Classifiers
Yan Aquino, Pedro Bento, Arthur Buzelin et al. Lecture notes in computer science, 2026. Cites: dataset

Forecasting 1-year atrial fibrillation risk from sinus rhythm electrocardiograms in arrhythmia-naïve patients
Nathan T. Riek, Tanmay Gokhale, Rui Qi Ji et al. Heart Rhythm O2, 2026. Cites: paper

Multimodal Fusion of Electrocardiogram Signals and Demographic Characteristics with Cross-Attention Networks in the Classification of Cardiovascular Diseases
Talip Çay, Emre ÖLMEZ. Gazi Üniversitesi Fen Bilimleri Dergisi Part C Tasarım ve Teknoloji, 2026. Cites: paper

Rhythm-Adaptive Recognition of ECG Pathologies Using Model-Informed Preprocessing and Classical Machine Learning Classifiers
Roman Butsiy, Serhii A. Lupenko, А. М. Зозуля. International Conference on Advanced Computer Information Technologies (ACIT), 2026. Cites: paper

Wolff–Parkinson–White syndrome screening from ECG via TinyFLFormer: A tensor-decomposed dual-stream transformer with diffusion-guided knowledge distillation
Majid Sepahvand, Maytham N. Meqdad. Intelligence-Based Medicine, 2026. Cites: paper

A Multimodal, Electrocardiography-Centric Clinical Data Platform With Artificial Intelligence-Assisted Querying for Cardiovascular Research
CARLOS RODRIGO RIVERO, Vicente Gallego Sánchez, Alejandro Cortés Beringola et al. Cureus, 2026. Cites: paper

A Novel Attention Mechanism (GAU) for TCNs in 3-to-12-Lead ECG Reconstruction
Mine ONAT, Yılmaz Kaya. Applied Sciences, 2026. Cites: paper

Federated acquisition-robust representation learning for cross-protocol ECG biometric authentication
Jiantao Xu, Dexing Zhou, Jianbo Xu et al. Pattern Recognition Letters, 2026. Cites: paper

AI-Assisted Multilabel Diagnosis of 12-Lead Electrocardiograms Using an Interpretable Stacked Deep Learning Model with External Validation
Asifa Tassaddiq, Aiman J.Albarakati, Rabab Alharbi et al. Diagnostics, 2026. Cites: paper

Next-Generation AI Architectures for ECG Arrhythmia Detection
Rajesh. S. Pashikanti. IGI Global eBooks, 2026. Cites: paper

Lead-Specific Pathological Sensitivity-Aware Multi-Lead ECG Abnormality Recognition
Dachuang Qin, Ziquan Feng, Jianfeng Liang et al. Information, 2026. Cites: paper

Leveraging ECG foundation models in critical care for sinus rhythm and atrial fibrillation classification
Maria Galanty, Michiel Hulleman, Merijn Constantijn Reuland et al. Intensive Care Medicine Experimental, 2026. Cites: paper

Robotic-Inspired Tri-Metaheuristic Framework with Neuromorphic Edge Intelligence for Real-Time Multi-Modal Biomedical Signal Processing and Clinical Decision Support
Shaymaa E. Sorour, Mostafa Elbaz. Research Square, 2026. Cites: paper

A deformable lead-attention fusion network for multi-label ECG classification integrating clinical metadata
Enjun Zhou, Xiangyong Kong, Hao Wang et al. Biomedical Physics & Engineering Express, 2026. Cites: paper

Ultra-low communication overhead federated learning strategy for distributed wearable ECG networks
Mohamed Naeem. Journal of King Saud University - Computer and Information Sciences, 2026. Cites: paper

Multi-label arrhythmia classification from Holter scatter plots using deep learning and clinically oriented thresholds
X W Chen, Jia Xu, Hui Li et al. Scientific Reports, 2026. Cites: paper

Objective Assessment of Pathological ECG Waveforms Using Gender-specific Normal Waveform Distributions
Krzysztof Piotr Malinowski, Klaudia K. Proniewska, Peter Michael van Dam. Arrhythmia & Electrophysiology Review, 2026. Cites: paper

From PhysioNet to foundation models—a history and potential futures
Gari D. Clifford. Physiological Measurement, 2026. Cites: paper

General-purpose time-series foundation models enable sample-efficient transfer learning in retinal electrophysiology
Hunter L. Porter, Cory B. Giles, Srividya Kottapalli et al. medRxiv, 2026. Cites: paper

A clinical decision support system for ECG diagnosis: Surpassing commercial standards through dual-stream feature fusion
ChuelWon Lee. Computer Methods and Programs in Biomedicine, 2026. Cites: paper

HRV-anchored autonomic-morphological structured factorization for interpretable multimodal cardiovascular risk prediction
Jiantao Xu, Dexing Zhou, Jianbo Xu et al. Computers in Biology and Medicine, 2026. Cites: paper

Reliability-aware hierarchical learning for Chagas disease screening from 12-lead ECGs: tackling label uncertainty and class imbalance
Hao Wen, Jingsu Kang. Physiological Measurement, 2026. Cites: paper

Inter-Patient Multi-Label Localization of Myocardial Infarction Territories Using 12-Lead ECG Signals
Ankita Shukla, Muhammed Izharuddin. Engineering Technology & Applied Science Research, 2026. Cites: paper

Optimization of generative-adversarial networks for the synthesis of electrocardiograms by adaptive quantization
Максим Михайлович Гордеев, A.E. Savkin, Olga P. Timofeeva et al. Herald of Dagestan State Technical University Technical Sciences, 2026. Cites: paper

Quantization-aware Mondrian conformal prediction for embedded ECG classification
Oussama El Allam, Mohamed Hamlich. Biomedical Signal Processing and Control, 2026. Cites: paper

A Hybrid Meta-Learning Framework Integrating ECG, Cine-MRI, and Biomarkers for Heart Failure Prediction
Wafa Baccouch, Narjes Benameur, Abdulrahman A. Alsayyari et al. Technologies, 2026. Cites: paper

Enhancing cardiovascular disease diagnosis through knowledge distillation and hybrid Transformer-CNN-SENet architecture
Nasim Beigzadeh, Abdolhossein Fathi. Journal of Medical Engineering & Technology, 2026. Cites: paper

Next-Generation AI Architectures for ECG Arrhythmia Detection From Signal Processing to Clinical Validation
Rajesh. S. Pashikanti. Advances in geospatial technologies book series, 2026. Cites: paper

Toward Standardized ECG Playback for Simulation-Based Interpretation Training: A Critical Narrative Review and Research Agenda
Fahmi M. Abu‐Owaimer, Sadeq Abu-Dawas, Loai Abu-Owaimer et al. Research Square, 2026. Cites: paper

BDFE-Net: Differential attention and bidirectional feature pyramids for robust multi-task ECG analysis
Zhaohui Yuan, Yuanyuan Deng, Wenhan Liu et al. Biomedical Signal Processing and Control, 2026. Cites: paper

Neuromorphic Cardiac Sensing: A Bio-Inspired Spiking Neural Network with Sensory-Adaptive Encoding for Energy-Efficient Arrhythmia Detection from ECG and PPG Signals
Cheng Ding, Jiahao Tian. Biomimetics, 2026. Cites: paper

As-ECTS: Adaptive Shapelet Learning for Early Classification of Streaming Time Series
Wei Li, Xiaofeng Meng. Lecture notes in computer science, 2026. Cites: paper

A Clinically Validated Explainable Federated Multi-Modal Learning Framework for Privacy Preserving Cardiac Arrhythmia Classification in Heterogeneous Data Environments
Bhargavi R, Johnson Kolluri. International Conference on Modern Sustainable Systems (CMSS), 2026. Cites: paper

A Cross-Attention Multimodal Fusion Framework for Heart Disease Prediction using Clinical and Electrocardiogram Data
Arockia Raj A., M. Arivukarasi. International Conference on Electronics and Sustainable Communication Systems (ICESC), 2026. Cites: paper

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