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

Distributional reliability explanation for diffusion-based electrocardiogram abnormality risk prediction
Chibuike Chiedozie Ibebuchi, Chinedu Ibebuchi. Machine Learning Health, 2026. Cites: dataset, 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

Software Frameworks for Explainable AI in Time Series Classification: A Systematic Review
Louis Peter, Nils Gumpfer, Jana Fischer et al. arXiv (Cornell University), 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

CardioState-JEPA: Delay-Aware Cross-Modal Learning of a Shared Cardiac Representation
Hamza Shafiq, Hung Manh Pham, Bin Zhu et al. arXiv (Cornell University), 2026. Cites: paper

Foundation models for movement data: Are they ready for prime-time?
Alexander Brauer, Benjamin Cauchi, Nils Strodthoff. arXiv (Cornell University), 2026. Cites: paper

Artificial intelligence-enabled electrocardiographic detection of acute occlusive myocardial infarction
Bjørn-Jostein Singstad, Bangin Turan, Jesper Ravn et al. Research Square, 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

Electrocardiogram Abnormality Classification From Summary Statistics With Patient‐Level Validation and Process‐Focused Evaluation
Sungjoon Hong, Christina Hartnett, Michael Ruane et al. Annals of Noninvasive Electrocardiology, 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

CFD-Guided Detection of Concept Drift in Multimodal Physiologic Signals
Farouk Ganiyu Adewumi, Timothy Oladunni, Rochak Ghimire et al. arXiv (Cornell University), 2026. Cites: dataset

Comparing CNN, Recurrent, Hybrid, and Transformer Models for Multi-Label ECG Classification on PTB-XL
Huey Phan. 2026. Cites: dataset

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: dataset, 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

Efficient ECG representation learning via intervention-based attribution alignment
Hongpo Zhang, Jiaang li, Yuan Li. Physiological Measurement, 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

AI-based Multi-Module Healthcare System for ECG Analysis, Body Metrics Evaluation, and Medicine Identification
N.N. Baalakumar, S. Prabakar, Nandhakumaran S et al. International Conference on Smart Systems for Electrical, Electronics, Communication and Computer Engineering (ICSSEECC), 2026. Cites: paper

ALTNet: A Transformer-Based Model for ECG Classification with Missing Leads
Khushi Gilhotra, Yogesh Lohumi, Durgaprasad Gangodkar. International Conference on Integrated Circuits, Communication, and Computing Systems (ICIC3S), 2026. Cites: paper

An Analysis of Explainable Artificial Intelligence for Intelligent Cybersecurity Applications
Mr. Raman Kumar. International Journal of Advanced Artificial Intelligence Research, 2026. Cites: paper

A Survey of Medical Vision-and-Language Applications and Their Techniques
Qi Chen, Ruoshan Zhao, Sinuo Wang et al. International Journal of Computer Vision, 2026. Cites: paper

Attention-Driven Hybrid Deep Learning Framework for Multi-Class ECG-Based Cardiovascular Disease Detection
Subbulakshmi M, M. Kanagavalli, Deenadhayalan R et al. 2026. Cites: paper

CARE-ECG: Causal Agent-based Reasoning for Explainable and Counterfactual ECG Interpretation
Elahe Khatibi, Ziyu Wang, Ankita Sharma et al. IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies, 2026. Cites: paper

Deep Learning Based ECG Signal Classification Using PTB-XL Dataset
K N Chaithra, Skanda S, Rachana J S et al. 2026. Cites: paper

ECG Time-Series Modeling Under Dataset Shift: A Structured Survey of Methods, Benchmarks, and Reliability Challenges
Mahira Tabassum Khan, Selena He. International Conference on Intelligent Multimedia, Networking, and Security (IMNS), 2026. Cites: paper

Ensemble of Hybrid CNN–RNN Architectures for Robust ECG Abnormality Classification
Plato Chakma, Md Jahangir Alam, Md Mahbub Hasan et al. International Conference on Smart Science and Technology (IncoSST), 2026. Cites: paper

Evaluation of ECG Leads in Myocardial Infarction Detection using 2-D Convolutional Neural Networks: Single, Addition-Subtraction, and Overlayed
Agung Wahyu Setiawan. International Electronics Symposium (IES), 2026. Cites: paper

MeDeA: Decomposable attention for intrinsically interpretable ECG diagnosis
Yulong GE, Yingying Wang, Qing Ming et al. Virtual Reality & Intelligent Hardware, 2026. Cites: paper

MSCAT-Net: Multi-Scale Cross-Attentive CNN-Transformer for ECG Classification
Jiayu Zhi, Duocai Jiang, Tian Liang et al. International Conference on Advanced Algorithms and Neural Networks (AANN), 2026. Cites: paper

Mutual Cross-Attention–Guided ECG-Report Alignment for ECG Representation Learning
Shuai Wang, Wei William Wang. IEEE International Conference on Smart Internet of Things (SmartIoT), 2026. Cites: paper

Performance Analysis of MELP, ZETA, and the Evidence-Gated Fusion Model on PTB-XL
Zhicheng Qiao. International Conference on Computer Vision and Data Mining (ICCVDM), 2026. Cites: paper

Resource-aware continuous ECG monitoring with selective cloud escalation and exact decision reuse
Mohammed Chaouqi, Latifa Doudach, Achraf Benba. Biomedical Physics & Engineering Express, 2026. Cites: dataset, paper

Sampling frequency has architecture-dependent effects on electrocardiogram deep learning classification: Convolutional neural networks are robust, whereas transformers benefit modestly
Cole Freedman, Syed Zawahir Hassan, Maximo Alvarez et al. Heart Rhythm, 2026. Cites: paper

Smart Myocardial Infarction Detection System Using Deep Learning, Ensemble Classifiers, and Explainable Artificial Intelligence from Single-Lead ECG Signals
Lamba Renuka, Maheswari K, Bagam Laxmaiah et al. IEEE World Conference on Applied Intelligence and Computing (AIC), 2026. Cites: paper

ViT-MI: Imbalance-Aware Vision Transformer Benchmarking for Multi-Class Myocardial Infarction Detection from ECG Images
Imelda Tyas Melati Kiyanayu, Satria Mandala, Santoso Wibovo. International Conference on Information Management and Technology (ICIMTech), 2026. Cites: paper

When PPG Meets ECG: Uncovering the Risks of Cross-Modal Biometric Matching
Linfeng Zhu, Kunning Shen, Chenhan Xu et al. IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies, 2026. Cites: paper

XAI-ECGFormer: Explainable Transformer-Based STEMI Detection Using 12-Lead ECG
T. Aditya Sai Srinivas, Sayyed Nagulmeera, Babalu Kushwaha et al. 2026. Cites: paper

A physics-driven deep unrolling framework with multiscale attention for multichannel Magnetocardiography denoising
Xiaokang Geng, Xiangyang Zhou, Changxu Zhu et al. Measurement, 2026. Cites: paper

Системный анализ трёхэтапной схемы сегментационного предобучения для выявления признаков инфаркта миокарда по электрокардиограмме в 12 отведениях
Сергей Анатольевич Атарщиков, Максим Юрьевич Орт, Конорева Наталья Анатольевна et al. Clinical and Fundamental Medicine, 2026. Cites: paper

A lightweight hybrid framework integrating convolutional neural networks and fast Fourier transform for reliable and calibrated ECG-based cardiac abnormality detection
Abdoul Malik, Selim Aras. PLoS ONE, 2026. Cites: paper

Benchmarking machine learning and deep learning models with a novel graph-attention SAGEConv-transformer for ECG arrhythmia detection
Motahareh Akbari Poodineh, fatemeh zare mehrjardi, Mohsen Sardari Zarchi. Scientific Reports, 2026. Cites: paper

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