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

MEETI: A Multimodal ECG Dataset from MIMIC-IV-ECG with Signals, Images, Features and Interpretations
Deyun Zhang, Lan Xiang, Shijia Geng et al. Scientific Data, 2026. Cites: paper

AI-ECG classification for Brugada syndrome: A study of machine learning techniques to optimise for limited datasets
Keenan Saleh, Raaif Hadadi, Yixiu Liang et al. PLOS Digital Health, 2026. Cites: paper

Four-electrode ECG reconstruction using anatomically grounded synthetic leads: a physiological measurement framework with hybrid CNN-transformer mapping
Rugved B. Parmar, Daoud Eldawud, Md Fahim et al. Physiological Measurement, 2026. Cites: paper

Toward Learning Shift-Invariant Representations for Healthcare Series Classification
Yuanbo Liu, Xiucheng Li, Xinyang Chen et al. IEEE Transactions on Knowledge and Data Engineering, 2026. Cites: paper

Cardiac health assessment across scenarios and devices using a multimodal foundation model pretrained on data from 1.7 million individuals
Xiao Gu, Wei Tang, Jinpei Han et al. Nature Machine Intelligence, 2026. Cites: paper

EQA-MDL: Wearable ECG Signal Quality Assessment via Multi-Scale Difference Learning
Haoyi Fan, Jiawei Luo, Huihui Chang et al. IEEE Journal of Biomedical and Health Informatics, 2026. Cites: paper

Localization of myocardial infarction based on omnidirectional vision feature aggregation driven by 3D point-clouds
Xianbin Zhang, Gui-bin Bian, Xiaoyun Zhang et al. Applied Soft Computing, 2026. Cites: paper

MERAC: Multimodal fusion of ECG and clinical report with local–global encoding for arrhythmia classification
Yunjie Jiang, Nan Wang, Qin Guo et al. Computational Biology and Chemistry, 2026. Cites: paper

MyoNet: intelligent feature engineering for precise early prediction of myocardial infarction
Abhishek Shrivastava, Santosh Kumar, Nenavath Srinivas Naik. Soft Computing, 2026. Cites: paper

A Systematic Pipeline of ECG Classification Using CWT and ECOC Meta-Learning
Gabrielle Villalba, Muhammad Sana Ullah. IEEE SoutheastCon, 2026. Cites: paper

CDM-DL-PSI: A conditional diffusion model for 12-Lead ECG generation using disease labels and patient-specific information
Rongjia Wang, Xunde Dong, Xiuling Liu et al. Biomedical Signal Processing and Control, 2026. Cites: paper

Machine Learning-Based ECG Signal Classification Using 1D Representation of the PTB-XL Dataset
Purnima Choudhary, Indu Saini. International Conference on Artificial Intelligence & Machine Learning in Communication and Power Systems (AIMLCPS), 2026. Cites: paper

ECGNextFormer: A Lightweight, Scalable, and Explainable Architecture for Estimating Cardiovascular Well-Being From Electrocardiograms
Mohammed Yusuf Ansari, Md. Rabiul Islam, Khalid A. Qaraqe et al. IEEE Transactions on Artificial Intelligence, 2026. Cites: paper

Position: Evaluation of ECG Representations Must Be Fixed
Zachary Berger, Daniel Prakah-Asante, John V. Guttag et al. arXiv (Cornell University), 2026. Cites: paper

A multi-label ECG classification algorithm based on self-supervised pretraining and multi-modal semantic alignment
Qian Wang, Weilun Meng, Congfan Gan et al. Biomedical Signal Processing and Control, 2026. Cites: paper

Artificial intelligence-based automated interpretation of images of electrocardiograms: development and multinational validation of ECG-GPT
Akshay Khunte, Veer Sangha, Evangelos K. Oikonomou et al. European Heart Journal - Digital Health, 2026. Cites: paper

Classification of paroxysmal atrial fibrillation using sinus rhythm electrocardiograms using the symmetric projection attractor reconstruction method
Steven Creasy, Gregory Y.H. Lip, Gary Tse et al. Scientific Reports, 2026. Cites: dataset, paper

CAMEL: An ECG Language Model for Forecasting Cardiac Events
Neelay Velingker, Alaia Solko-Breslin, Mayank Keoliya et al. PubMed Central, 2026. Cites: paper

A Novel Self-Supervised Learning Based on Masked Signal Modeling for Multimodal Physiological Emotion Recognition
Xin Wan, Yongxiong Wang, Zhe Wang et al. IEEE Sensors Journal, 2026. Cites: paper

A Cognitive Risk Taxonomy for AI-Assisted Emergency ECG Interpretation: Mapping Algorithmic Error to Physician Bias Pathways
Al-Baraa Dabaliz, Al-Awwab M. Dabaliz, Mosab Hawarey. 2026. Cites: paper

Near-instantaneous Cardiovascular Event Prediction Using Multimodal Deep Learning
Maytham Al-Hasooni, Amenah Abdzaid, Noor Hadi et al. Electronics ETF, 2026. Cites: paper

Smart Optogenetics for Real‐Time Automated Control of Cardiac Electrical Activity
Shanliang Deng, Niels J. Harlaar, Juan Zhang et al. Advanced Science, 2026. Cites: paper

MAR-GCNet: Multi-label abnormal detection of electrocardiograms by combining multiscale features and graph convolutional networks
Kan Luo, Haixin He, Yu Chen et al. Biomedical Signal Processing and Control, 2026. Cites: paper

ECG-AuxNet: A Dual-Branch Spatial-Temporal Feature Fusion Framework With Auxiliary Learning for Enhanced Cardiac Disease Diagnosis
Ruiqi Shen, Yanan Wang, Chunge Cao et al. IEEE Journal of Biomedical and Health Informatics, 2026. Cites: paper

ETS-MLLM: A large time series-language model for electrocardiogram question answering
Jinning Yang, Zhile Yang, Jiajing Zhou et al. Expert Systems with Applications, 2026. Cites: paper

Clinically Aligned Explainable AI Improves Myocardial Infarction Detection Using Multi-Lead Electrocardiography
Amirsajjad Taleban, Rodney Sparapani, Sharon Zlochiver et al. Research Square, 2026. Cites: paper

From Motion Artifacts to Clinical Insight: Multi-Modal Deep Learning for Robust Arrhythmia Screening in Ambulatory ECG Monitoring
Pierre Boulanger. Sensors, 2026. Cites: paper

Modality-Agnostic Hybrid Federated Learning via Knowledge Distillation and Reinforcement Learning-Based Aggregation
Chen Wang, Yongli Hu, Huajie Jiang et al. IEEE Transactions on Circuits and Systems for Video Technology, 2026. Cites: paper

Paced ECG classification with pacing pulse-preserving mechanism and hybrid data augmentation
Zongyu lv, Ruiwen Li, Mingjie Wang et al. Physica Scripta, 2026. Cites: paper

Study of the Structure and Function of the Human Heart Using Non-Invasive Measurements
Mikhail Nikolaevich Ustinin, A.E. Sidorova, E.A. Sapelnikov et al. Mathematical Biology and Bioinformatics, 2026. Cites: paper

ACL-ECG: Anatomy-Aware Contrastive Learning for Multi-Lead Electrocardiograms
Wenhan Liu, Zhijing Wu, Zhaohui Yuan. Sensors, 2026. Cites: paper

A hybrid learning framework for automated multiclass electrocardiogram classification with SimCardioNet
Muhammad Dawood Majid, Muhammad Anwar, Syed Fakhar Bilal et al. Scientific Reports, 2026. Cites: paper

An Optimized Multimodal Deep Learning Framework for Accurate Detection of Cardiac Arrhythmia
Akkaraju Vidyullatha, Rajasekar M, Anitha Gopalan. Contemporary Computing Innovations Conference (CCIC), 2026. Cites: paper

xGNN4MI: explainability of graph neural networks in 12-lead electrocardiography for cardiovascular disease classification
M. Mäurer, Philip Hempel, Kristin Elisabeth Steinhaus et al. npj Digital Medicine, 2026. Cites: paper

Closed-form feedback-free learning with forward projection
Robert O'Shea, Bipin Rajendran. Nature Communications, 2026. Cites: paper

Robust multilabel ECG classification under class imbalance using augmentation and adaptive iterative training
Joshua Tiffany, Qi Zhang. Biomedical Signal Processing and Control, 2026. Cites: paper

A Lightweight Multi-Stream Baseline for Multi-Label ECG
Huda Mustafa Radha, Umniah Hameed Jaid. International Conference on Computing and Emerging Sciences, 2026. Cites: paper

PhysioBridge: Physiology-Constrained Self-Supervised Foundation Model for Cross-Device ECG–PPG Learning with Conformal Risk Control
A H Alzubaidi, Ali Al-Shuwaili, Ali Al-Bayaty. International Conference on Computing and Emerging Sciences, 2026. Cites: paper

A Systematic Review of Contrastive Learning in Medical AI: Foundations, Biomedical Modalities, and Future Directions
George Obaido, Ibomoiye Domor Mienye, Kehinde Aruleba et al. Bioengineering, 2026. Cites: paper

ECG-XAI: Attention-ResNet1D for Multi-Label Cardiac Diagnosis with Explainability
Hawraa Hotiet, Marwan Alhawat, Mohamad Abou Ali et al. IEEE Mediterranean Electrotechnical Conference (MELECON), 2026. Cites: paper

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

CardioFusionNet: A Multimodal Deep Learning Framework for Enhanced Coronary Artery Disease Diagnosis
Zhiyong Tao, Yiwei Zhang, Shize Pan. International Conference on Artificial Intelligence, Digital Media Technology and Social Computing (ICAIDS), 2026. Cites: paper

End-to-End Platform for Electrocardiogram Analysis and Model Fine-Tuning: Development and Validation Study
Lucas Bickmann, Lucas Plagwitz, Antonius Büscher et al. Journal of Medical Internet Research, 2026. Cites: paper

Metric Hub: A metric library and practical selection workflow for use-case-driven data quality assessment in medical AI
Katinka Becker, Maximilian P. Oppelt, Tobias S. Zech et al. arXiv (Cornell University), 2026. Cites: paper

RWT-Net: A hybrid ResNet-wavelet-transformer for early detection of left ventricular hypertrophy
Hoang Huu To Nguyen, Phuong Huu Nghia Le, Lam Mai et al. TELKOMNIKA (Telecommunication Computing Electronics and Control), 2026. Cites: paper

SLPM: a lightweight deep learning model for end-to-end paper ECG digitization
Xiankai Yu, Jian Wu, Jiahao Wang et al. Physiological Measurement, 2026. Cites: paper

The Evolving Role of Artificial Intelligence and Machine Learning in the Wearable Electrocardiogram: A Primer on Wearable-Enabled Prediction of Cardiac Dysfunction
Aditya Dave, Amartya Dave, Issam D. Moussa. Bioengineering, 2026. Cites: paper

Deep Learning Decodes Latent ECG Signatures of Stress Cardiomyopathy
Jooyoung Ryu, Carl Harris, Chenjia Zhang et al. medRxiv, 2026. Cites: paper

ELOGOnet: Knowledge-enhanced local-global learning for cardiac diagnosis
Yizhuo Feng, Beibei Wang, Zirui Wang et al. Information Fusion, 2026. Cites: paper

Unsupervised electrocardiogram signal denoising and quality assessment using spectrum-constrained cycle-consistent generative adversarial network
Meng Chen, Yongjian Li, Mingsen Du et al. Engineering Applications of Artificial Intelligence, 2026. Cites: paper

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