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

Masked Generative Distillation for Robust Multi‐Lead‐to‐Single‐Lead ECG Classification on IoMT Devices
Anandu Shivakumar, Obada Al-Khatib, Ghalia Nassreddine et al. Healthcare Technology Letters, 2026. Cites: dataset

MCCGAA: Multimodal Channel Compression Graph Attention Alignment Network for ECG Zero-Shot Classification
Qiuxiao Mou, Haoyu Gui, Xianghong Tang et al. Computers, materials & continua/Computers, materials & continua (Print), 2026. Cites: paper

Multi-modal Biometric Authentication Based on Deep Adversarial Learning Utilizing ECG and Fingerprint Modality
Abdullah Alduhailan, Nazhatul Hafizah Kamarudin, Siti Norul Huda Sheikh Abdullah et al. Journal of Advances in Information Technology, 2026. Cites: paper

Patient-Level Out-of-Fold-Guided Threshold-Aware Heterogeneous Convolutional Neural Network–XGBoost Probability Fusion for Identification of Atrial Fibrillation from PTB-XL
Poonam Chhabra, Rosy Madaan. Advances in Artificial Intelligence and Machine Learning, 2026. Cites: paper

Post-Pandemic Generalization of a Deep-Learning ECG Biomarker of Sudden Cardiac Death: A Pre-Registered Replication and Extension Testing Convergent Electrical Remodelling and COVID-19 Substrate Shift
Amr Ahmed, Khulood Almatuiri. 2026. Cites: paper

Retrieval-Augmented Multi-modal Representation Learning for ECG Analysis
S Wang, Zhaoming Pang, Xinzhu Xu et al. Lecture notes in computer science, 2026. Cites: paper

Revisting Data-Driven ECG Classification: Definitions, Datasets and Benchmarks
Chengwei Zhang, Guipeng Wei, Dan Li. Communications in computer and information science, 2026. Cites: paper

TCNA: A Temporal Convolutional Network With Attention for Real-Time Multi-Class ECG Classification at the Edge
Aicha Aggoune. IEEE Access, 2026. Cites: paper

Temporal Fusion Transformers for Forecasting ECG Signals
Fatima Sajid Butt, Chitra Khatri, Aniket Prakash Nighot et al. Communications in computer and information science, 2026. Cites: paper

Transformer-Based Generative Adversarial Network With Multi-Scale Temporal Attention for ECG Synthesis and PQRST Feature Preservation
Ayswarya R Kurup, Mithun Kumar Kar, Madhusudhan Mishra et al. IEEE Access, 2026. Cites: paper

Transformer Encoder Driven Deep Learning Network for Single Lead ECG Arrhythmia’s Across 21837 Records
Sureshkumar Sundaramoorthy, Govardhan Karunanidhi. IEEE Access, 2026. Cites: paper

TS-P$$^2$$CL: Plug-and-Play Dual Contrastive Learning for Vision-Guided Medical Time Series Classification
Qi’ao Xu, Pengfei Wang, Bowen Zhong et al. Lecture notes in computer science, 2026. Cites: paper

VCP: Visible Context Propagation for Electrocardiogram Recovery
Jaeho Park, Yong‐Yeon Jo, Jong-Hwan Jang et al. IEEE Open Journal of Signal Processing, 2026. Cites: paper

When and How to Focus: A Task-Dependent Analysis of Efficient Attentive Architectures for Biosignal Classification
Rami Zewail. IEEE Access, 2026. Cites: paper

Моделі машинного навчання для раннього виявлення аритмій за ЕКГ
В. С. Матеуш. Repository of Vinnytsia National Technical University (Vinnytsia National Technical University), 2026. Cites: paper

Organic Electrochemical Random Access Memory: From Bio‐Inspired to Bio‐Integrated
Shijie Wang, Bingjun Wang, Xinru Teng et al. Advanced Materials, 2025. Cites: paper

Versatile cardiovascular signal generation with a unified diffusion transformer
Zehua Chen, Yuyang Miao, Liyuan Wang et al. Nature Machine Intelligence, 2025. Cites: paper

Foundation models for electrocardiogram interpretation: clinical implications
Alexis Nolin-Lapalme, Achille Sowa, Jacques Delfrate et al. European Heart Journal, 2025. Cites: paper

Multi-label ECG diagnosis via adversarial view decoupling and hierarchical label constraints
Weilun Meng, Qian Wang, Congfan Gan et al. Knowledge-Based Systems, 2025. Cites: paper

MedNet: A Medical Overview-Focus Network With Uncertainty-Regularized Loss for Unsupervised ECG Anomaly Detection
Zhe Zhang, Jiongwen Chen, Gang Jin et al. IEEE Journal of Biomedical and Health Informatics, 2025. Cites: paper

A novel adaptive CNN-LSTM fusion network for electrocardiogram diagnosis
Yuxuan Wu, Jijun Tong, Pengjia Qi. Physiological Measurement, 2025. Cites: paper

Intra-Lead ECG Analysis for Deepfake Detection Using Temporal Neural Networks
Mallikarjun Yeshlur, Manthan B T, Ammaar Mohammed Faiz et al. IEEE India Conference, 2025. Cites: paper

Theoretical Perspective on Histogram Binning with Extension to Multi-label Medical Image Classification
Arkapal Panda, Aditya Shankar Pal, Utpal Garain. Indian Conference on Computer Vision, Graphics and Image Processing, 2025. Cites: paper

A Personalized Transfer Learning Framework for Myocardial Infarction Localization
Zhe Wang, Shuaiying Yuan, Yongkang Qin et al. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025. Cites: paper

BiECG-LLM: An Approach to ECG Classification and Report Generation Using a Fine-Tuned LLM with Bi-Modal ECG
Yupeng Qiang, Xunde Dong, Xiuling Liu et al. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025. Cites: paper

ECG-Expert-QA: A Benchmark for Evaluating Medical Large Language Models in ECG
Xu Wang, Jiaju Kang, Puyu Han et al. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025. Cites: paper

Enhancing Contrastive Learning-Based Electrocardiogram Pretrained Model with Patient Memory Queue
Xiaoyu Sun, Yang Yi, Xunde Dong. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025. Cites: paper

Enhancing ECG Movement Artifact Filtering for Unseen Data Through Denoising Autoencoders
Giorgio de Moraes Rossa, Emely Pujólli da Silva, Marcelo S. Reis. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025. Cites: paper

LGFDTK-RAG: Dual-Conditioned RAG with Label-Guided Filtering and Dynamic Top-K for Automated ECG Report Generation
Fei Hu, Xunde Dong, Xiuling Liu et al. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025. Cites: paper

MTA-Net: A Multi-Scale Temporal-Attentive Network with Semantic-Structural Fusion for Multi-Label ECG Classification
Shanchen Pang, Zite Kan, Zhiyuan Zhao et al. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025. Cites: paper

Multi-Granular Temporal-Spatial Modeling: A Dual-Modality Framework for Fusing ECG Sequences and Visual Representations
Shuang Wang, Zhaoming Pang, Li Zhang et al. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025. Cites: paper

PSE-KANet: A Spectrum Enhanced Spline-Adaptive Network for Multi-Label ECG Classification
Lei Guo, Shangjin Yang, Ying An. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025. Cites: paper

SPG-Net: A Structure-Aware Spatiotemporal Graph Neural Network for Electrocardiogram-Based Myocardial Infarction Localization
Ying An, Ke Du, Xianlai Chen et al. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025. Cites: paper

STELLAR: Pacemaker Recognition Using 12-Lead ECG and Spatio-Temporal Harmonic Mechanism
Han Zhang, Zeyuan Ding, Leping Yang et al. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025. Cites: paper

Thinking Like a Cardiologist: Unifying Patient Context and Spatiotemporal Dynamics via Heterogeneous Graph
Yiran Chen, Shuo Yang, Yisu Liu. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025. Cites: paper

A Systematic Literature Review of Retrieval-Augmented Generation: Techniques, Metrics, and Challenges
Andrew Brown, Muhammad Roman, Barry J. Devereux. Big Data and Cognitive Computing, 2025. Cites: paper

Deep Learning Approaches for Classifying ECG Images with CNN and Transfer Learning
J Kavi Preethi, Deva Priya Isravel, Julia Punitha Malar Dhas. International Conference on Smart Structures and Systems (ICSSS), 2025. Cites: paper

Detection of Chagas Disease Using Digital Electrocardiogram by Deep Transfer Learning of the InceptionTime Model
Arnaud Champetier, Christian Eugen Mueller. Computing in cardiology, 2025. Cites: paper

Diagnostic ECG Classification of Myocardial Infarction and ST-T Changes Using Machine Learning via 3D Vectorcardiogram Data
Lucenildo Silva Cerqueira, Jurandir Nadal. Computing in cardiology, 2025. Cites: dataset, paper

One-Dimensional ConvNeXt for Chagas Disease Screening from 12-Lead ECGs
Elaine Li. Computing in cardiology, 2025. Cites: paper

On Spurious Features When Predicting Chagas
Matthew DuPont, Richard J. Povinelli. Computing in cardiology, 2025. Cites: paper

Rethinking driver fatigue detection as anomaly identification: A hypergraph-transformer approach
Jwu‐Sheng Hu, Hao Yuan, B. Li et al. Information Processing & Management, 2025. Cites: paper

Accelerating Machine Learning in Healthcare: Addressing the Labelling Bottleneck
Spencer Vecile, William Gregory Dixon, Azadeh Assadi et al. Research Square, 2025. Cites: paper

Efficient Neural Architectures for Real-Time ECG Interpretation on Limited Hardware
Ashery Mbilinyi, Callum O'Riley, Julia Handra et al. IEEE International Conference on Big Data (BigData), 2025. Cites: paper

Efficient and Interpretable ECG Abnormality Detection via a Lightweight DSCR-BiGRU-Attention Network with Demographic Fusion
Kan Luo, Longying Huang, Hongjie He et al. Mathematics, 2025. Cites: paper

Versatile and Risk-Sensitive Cardiac Diagnosis via Graph-Based ECG Signal Representation
Yue Wang, Yuyang Xu, Renjun Hu et al. IEEE Transactions on Big Data, 2025. Cites: paper

A dual-stage framework for cardiovascular abnormalities diagnosis from ECG signals using CA-GNN and semi-supervised autoencoders
Nur Mohammad Fahad, Md. Abdur Rahman, Md. Jakarea et al. Signal Image and Video Processing, 2025. Cites: paper

Conditional Electrocardiogram Generation Using Hierarchical Variational Autoencoders
Ivan Sviridov, Konstantin Egorov. Automatic Documentation and Mathematical Linguistics, 2025. Cites: paper

High-accuracy ECG image interpretation using parameter-efficient Low-Rank Adaptation (LoRA) fine-tuning with multimodal LLaMA V.3.2
Nandakishor Mukkunnoth, Anjali Mukkunnoth, Meenakshi P. Khapre et al. BMJ Digital Health & AI, 2025. Cites: paper

Machine learning for classification of advanced rheumatic heart disease using electrocardiogram in cardiology ward
Amsalu Tomas Chuma, Melkamu Hunegnaw Asmare, Carolina Varon et al. BMC Cardiovascular Disorders, 2025. Cites: paper

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