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

Distinguishing Suspicious Brugada from Benign RBBB: Binary and Multi-Class Evaluation with a Lightweight CNN on Leads $\mathrm{V}_{1}$ and $\mathrm{V}_{6}$
Alessandro Casella, Vincenzo Randazzo, Carla Giustetto et al. IEEE International Instrumentation and Measurement Technology Conference, 2026. Cites: paper

How Well Can Vision-Language Models Interpret ECGs? A Multi-Model and Multi-Representation Investigation of Zero-Shot Arrhythmia Classification
Ke Du, Joseph Azar, Jiaxing Yan et al. International Conference on Computer, Control and Robotics (ICCCR), 2026. Cites: paper

Multi-Agent Large Language Model Framework for Comprehensive ECG Signal Analysis: Delineation, Classification, and Arrhythmia Subtyping with Temporal Hierarchical Reasoning
Mohsen Avesta, Maedeh Avesta, Asma Yousefian Baboukani et al. 2026. Cites: paper

Training Strategies for Imbalanced Single-Task and Multitask Electrocardiogram Classification
Joshua Tiffany, Qi Zhang. Conference proceedings - Canadian Conference on Electrical and Computer Engineering, 2026. Cites: paper

AI-enabled multi-omics integration in colorectal cancer: from molecular stratification to clinical translation
Honghua Su, Tiangui Wang, Chaofan Chen. Frontiers in Cell and Developmental Biology, 2026. Cites: paper

DiffTS-Med: a diffusion-based framework for multimodal medical time series generation, imputation, and forecasting
Ziyan Yan, Jiabin Liang, Chenyu Li et al. Biomedical Signal Processing and Control, 2026. Cites: paper

A transformer encoder-based multi-feature branch network for myocardial infarction localization
Peng Xiong, Shiqi Ma, Wenjun Xie et al. International Journal of Data Science and Analytics, 2026. Cites: paper

MIMIC-III-Ext-PPG, a PPG-based Benchmark Dataset for Cardiovascular and Respiratory Signal Analysis
Mohammad Moulaeifard, Marie Kutscher, Philip J. Aston et al. Scientific Data, 2026. Cites: paper

The Rlign algorithm for enhanced electrocardiogram analysis through heart rate–corrected ECG alignment for explainable classification and clustering
Lucas Plagwitz, Lucas Bickmann, Michael Fujarski et al. European Heart Journal - Digital Health, 2026. Cites: paper

A 10.1-ENOB 8kHz Bandwidth 95--250nW PVT-Robust DT Level-Crossing ADC for Sparse and Generic Signals
Jixuan Mou, Pieter J. A. Harpe, Alessandro Saccon et al. IEEE Journal of Solid-State Circuits, 2026. Cites: paper

A self-supervised electrocardiogram foundation model for empowering cardiovascular disease prediction and genetic factor discovery
Siying Lin, Zhaoqi Li, Qifan Wu et al. Nature Communications, 2026. Cites: paper

HeartBERT: A self-supervised ECG embedding model for efficient and effective medical signal analysis
Saedeh Tahery, Fatemeh Hamid Akhlaghi, Termeh Amirsoleimani et al. Computers in Biology and Medicine, 2026. Cites: paper

Domain-Adapted Fine-Tuning of ECG Foundation Models for Multi-Label Structural Heart Disease Screening
Duc N. Do, Minh N. Do, Dang H. Nguyen et al. arXiv (Cornell University), 2026. Cites: paper

Self-organized channel attention network for myocardial infarction detection from single-lead ECG
Junming Zhang, Yushuai Wang, Yuxiao Peng et al. Biomedical Signal Processing and Control, 2026. Cites: paper

ML-PatchTST: A Spatio-Temporal Joint Patch Attention Network for Multi-Lead ECG Arrhythmia Classification
Xianfeng Xia, Qin Wei. International Conference on Electronic Information Engineering, Big Data and Computer Technology (EIBDCT), 2026. Cites: paper

On the generation of 12-channel electrocardiograms based on a hybrid of diffusion and graph neural network models
Evgeniy Schetinin, Anna V. Pestryakova, Julia Georgievna Shatalova et al. VESTNIK OF ASTRAKHAN STATE TECHNICAL UNIVERSITY SERIES MANAGEMENT COMPUTER SCIENCE AND INFORMATICS, 2026. Cites: paper

Cardiovascular Risk Prediction Using ECG via a Time–Frequency Embedding Pre-Trained Model
Junhao Lin, Guanhua Ren, Changhong Jing et al. IEEE Transactions on Consumer Electronics, 2026. Cites: paper

PhysioKey: Edge-AI-Driven Physiological Key Agreement for Secure Body Area Networks
Mohammed Hassan Alnemari, Osamah M. Al-Omair. Sensors, 2026. Cites: paper

A clinically-oriented XAI framework for arrhythmia triage via Hierarchically-Decomposed Neural Attribution: From dual-stream interpretation to risk stratification
Yusen Wu, Jinde Zhu, Junhao Yuan et al. Computational Biology and Chemistry, 2026. Cites: paper

An End to End Hybrid CNN and LSTM Framework for ECG Classification with Demographic and Statistical Insights on QT and QRS Dynamics
Maitreya Moola, Abhirup Basu, Mayank Kishor et al. International Conference on Recent Advances in Electrical, Electronics, Ubiquitous Communication, and Computational Intelligence (RAEEUCCI), 2026. Cites: paper

Unsupervised phenotype discovery in 12-lead ECGs using deep multimodal clustering techniques
Ridwan Salahudeen, Shengwu Xiong, Aishah A. Muhammad et al. Biomedical Signal Processing and Control, 2026. Cites: paper

AdaGrad-Fusion: Adaptive Gradient Fusion for Memory-Efficient ECG Foundation Model Fine-Tuning
Chenyang Xu, Yi Zhao, Z Zhang et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2026. Cites: paper

AutoLeadX: A Unified Framework for Arbitrary Reduced-Lead to Standard 12-Lead ECG Reconstruction
Ya-Hsuan Chu, I-Fan Chen, Yujia Wu et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2026. Cites: paper

A Video Perspective on Electrocardiograms: Attention-Based Spatiotemporal Modeling
Cunnan Wei, Yanjie Lu, Hong Sun et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2026. Cites: paper

CG-DMER: Hybrid Contrastive-Generative Framework for Disentangled Multimodal ECG Representation Learning
Ziwei Niu, Hao Sun, Shujun Bian et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2026. Cites: paper

Cross-Modality Self-Supervision for Unimodal Physiological Signals Representation Learning
Xiaomao Fan, Shuangdu Li, Jikui Liu et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2026. Cites: paper

ECG-Agent: On-Device Tool-Calling Agent for ECG Multi-Turn Dialogue
Hyunseung Chung, J H Oh, Daeun Kyung et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2026. Cites: paper

ECG TransNet: Intra/Inter-Lead Feature Integration with Proxy-Guided Learning for 12-Lead ECG Classification
Jaebin Cha, Junyeong Heo, Ryuha Kim et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2026. Cites: paper

Enhancing Inter-Lead Correlations: A Novel Diffusion GAN Framework for 12-Lead ECG Generation
Yongchao Wang, Guo F, Shizhan Tang et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2026. Cites: paper

From ECG Signals to Diagnostic Reports: A Unified Framework with Multimodal Encoder and Fine-Tuned LLM for Automated Report Generation
S Wang, Zhaoming Pang, S Wang et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2026. Cites: paper

Physiologically Informed Attention: Tackling Class Imbalance in Myocardial Infarction Localization with an ST-Segment Guided Transformer
Yiran Chen, Shuo Yang, Yisu Liu et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2026. Cites: paper

RhythmBERT: A Self-Supervised Language Model Based on Latent Representations of ECG Waveforms for Heart Disease Detection
Xin Wang, Burcu Ozek, Aruna Mohan et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2026. Cites: paper

Robust Multimodal Representation Learning in Healthcare
Xiaoguang Zhu, Linxiao Gong, L. C. Sun et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2026. Cites: paper

Seam-Former: Infusing Waveform Semantics into Transformers for Explainable Myocardial Infarction Localization via 12-Lead ECG
Yuhang Liu, Fan Lin, Qiang Xie et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2026. Cites: paper

Deep Learning-Based ECG Retrieval for Scalable Clinical Decision Support
Varshika Rajesh, R. Prathanyaasree, Vishal. U et al. International Conference on Communications and Signal Processing (ICCSP), 2026. Cites: paper

Low-latency HRV analysis from ultra-short ECG windows using a modular deep-learning framework
Jan Dobrosolski, Julian Szymański, Dariusz Kozłowski. Scientific Reports, 2026. Cites: paper

A Multi-Label Electrocardiogram Classification Study Integrating Clinical Metadata and Channel Attention
Jiajing Sun, Ying Sun, Jiang Zhao et al. Journal of Computer Science and Frontier Technologies, 2026. Cites: paper

Electrocardiogram classification method based on nonlinear spiking neural convolutional and echo-like recurrent models
Junxian Xiao, Jianbin Yan, Bing Li et al. Biomedical Signal Processing and Control, 2026. Cites: paper

ECG Classification Model Based on Multi-View Image Fusion
Yue Zongzhen, Xudong Zhu, Peihao Zhang et al. International Conference on Biomedicine and Bioinformatics Engineering (ICBBE), 2026. Cites: paper

EchoNext-Mini: A Dataset and Baseline AI Model for Detecting Structural Heart Disease from Electrocardiograms
John Weston Hughes, Linyuan Jing, Joshua Finer et al. NEJM AI, 2026. Cites: paper

A Clinically Alinigned ResNet-1D Framework for Robust Myocardial Infarction Detection Using 12-Lead ECG Signals
Chennaiah Kate, Mothe Rakesh, Alpha Vijayan et al. International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering (RMKMATE), 2026. Cites: paper

A New Multi-Class Framework for Electrocardiogram Arrhythmia Classification Using Artificial Intelligence
Mohammad Zuhair Abo Hadba, Amira J. Zaylaa, Mohammad Ayache. IEEE International Multidisciplinary Conference on Engineering Technology (IMCET), 2026. Cites: paper

Fusion of RR Interval Dynamics and HRV Multidomain Signatures Using Multimodal Neural Models for Metabolic Syndrome Classification
Miguel A. Mejia, Oscar J. Suárez, Gilberto Perpiñán et al. Medical Sciences, 2026. Cites: paper

Editable XAI: Toward Bidirectional Human-AI Alignment with Co-Editable Explanations of Interpretable Attributes
Haoyang Chen, Jingwen Bai, Fang Tian et al. CHI Conference on Human Factors in Computing Systems, 2026. Cites: paper

Stabilizing Extreme Few‐Shot ECG Classification via Self‐Supervised Contrastive Pretraining
LiuPing Zeng, Jingmei Pan, YangJie Lu et al. Annals of Noninvasive Electrocardiology, 2026. Cites: paper

FPECGNET: A deep learning framework based on federated learning and prototype learning for interpretable ECG classification with privacy
Jiang He, Jie He, Jin Xiong et al. iScience, 2026. Cites: paper

An Enhanced Deep Learning Framework for Predicting Risk Levels of Heart Disease Using Multimodal Data
Manpreet Kaur, Rohini Mahajan, Amandeep Kaur et al. International Conference on Computing for Sustainable Global Development, 2026. Cites: paper

BEAT-SSL: Capturing Local ECG Morphology Through Heartbeat-Level Contrastive Learning with Soft Targets
Muhammad Ilham Rizqyawan, Peter W. Macfarlane, Stathis Hadjidemetriou et al. IEEE International Symposium on Biomedical Imaging (ISBI), 2026. Cites: paper

MultiECGNet: Evaluation of a Deep-Learning Ensemble Method for Image-Based 12-Lead Electrocardiographic Detection of Atrial Fibrillation
George Parker, Justin Anh-Kiet Phan, Nigel Hamilton Lovell et al. CJC Open, 2026. Cites: paper

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