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

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

Formal Runtime Verification Framework for Detecting Cardiac Abnormalities
Hemant Sastry Konduri, Ayush Anand, Srinivas Pinisetty et al. IEEE Embedded Systems Letters, 2026. Cites: paper

Integrated Machine Learning and Deep Learning Framework for Cardiovascular Disease Prediction from ECG Images
Mrs B. Sushma, Karnati Akanksha, Siripuram Rahul. et al. International Conference on AI-Driven Smart Systems and Ubiquitous Computing (ICAUC), 2026. Cites: paper

Contactless 12-lead electrocardiogram via deep computational radar
Zhi Peng Lu, Jinbo Chen, Dongheng Zhang et al. npj Biomedical Innovations., 2026. Cites: paper

FedMCF-xLSTM: Federated contrastive xLSTM for multimodal multi-label ECG classification
Eryang Huan, Hui Dun, Junbao Li. Biomedical Signal Processing and Control, 2026. Cites: paper

A Knowledge-Guided Feature Fusion and Fuzzy Decision Integration Model for ECG-Based Cardiovascular Disease Diagnosis
Yuepeng Chen, Shangce Gao, Jiaru Yang et al. IEEE Transactions on Fuzzy Systems, 2026. Cites: paper

Application of Graph Neural Networks on ECG Data: A Systematic Literature Review
Alissa Müller, Manuel Scheibl, Tobias Uhe et al. IEEE Journal of Biomedical and Health Informatics, 2026. Cites: paper

Dynamic Cardiac Event Detection From Single-Arm Wearable ECG via a Contrastive Multitask Framework
Xianbin Zhang, Haoke Zhang, Gui‐Bin Bian et al. IEEE Transactions on Biomedical Engineering, 2026. Cites: paper

Federated learning with homomorphic encryption for secure real time ECG anomaly detection: A multi institutional privacy preserving framework
Beyazit Bestami Yuksel, Ayse Yilmazer Metin. Biomedical Signal Processing and Control, 2026. Cites: paper

ProtoKDM: An interpretable prototype-based framework for biomedical time-series analysis
Alber Montenegro, Fabio A. González, Hugo Franco. Biomedical Signal Processing and Control, 2026. Cites: paper

Interpretable multimodal zero shot ECG diagnosis via structured clinical knowledge alignment
Jialu Tang, Huy Pham, I L J De Lathauwer et al. npj Cardiovascular Health, 2026. Cites: paper

Benchmarking machine learning for bowel sound pattern classification – From tabular features to pretrained models
Zahra Mansour, Verena Uslar, Dirk Weyhe et al. PLoS ONE, 2026. Cites: paper

Integrated ECG IoT-Based Health Monitoring Using Machine Learning
Gurusigaamani Ayyanar Muthulingam, Kardeepa Ponnuchamy, Bojjireddy Prathyusha et al. International Conference on Smart Futuristic Technology (SMARTTECH), 2026. Cites: paper

A Deep Learning Model for Advanced Driver Assistance Systems Scenario Detection
Federico Izzi, Massimo Cafaro, Italo Epicoco. SSRN Electronic Journal, 2026. Cites: paper

Anomaly-Selective Conformal Calibration for ECG Monitoring: Threshold Divergence and the Limits of Finite-Sample False Alarm Control
Sangwook Sim, Changgyun Kim. IEEE Access, 2026. Cites: paper

Are ECGs Enough? Deep Learning Classification of Pulmonary Embolism Using Electrocardiograms
João D. S. Marques, Arlindo L. Oliveira. Lecture notes in computer science, 2026. Cites: paper

A Review of Deep Learning Methods for Irregularly Sampled Medical Time Series Data
Chenxi Sun, Moxian Song, Derun Cai et al. Health Data Science, 2026. Cites: paper

Atrial Fibrillation and Arrhythmia Classification Using 12-Lead ECG: Comparing ML Models
Ismaeel Al Ridhawi, Hasan Fayyad-Kazan, Ali Abbas. Lecture notes in electrical engineering, 2026. Cites: paper

Bionic Wearable ECG with Multimodal Large Language Models: Coherent Temporal Modeling for Early Ischemia Warning and Reperfusion Risk Stratification
Songtao An, Jiamin Yuan, Yang Pan et al. Cyborg and Bionic Systems, 2026. Cites: paper

Boosting ECG Classification Performance by Pre-training with Synthesized Data
Naoki Nonaka, Jun Seita. Communications in computer and information science, 2026. Cites: paper

CaLiNet-E: Reconstructing 12-lead ECG from three leads with brief patient-specific calibration
Xinyu Zhang, Ran Xin, Hailing Cai et al. SSRN Electronic Journal, 2026. Cites: paper

Cardiac Disease Detection from Electrocardiogram Signals Using Transformers: A Multimodal Deep Learning Approach
Cristinel-Gabriel Rusu, Keka C. Biswas, Luminița Moraru. Lecture notes in networks and systems, 2026. Cites: dataset

CardioMex-Q: A Clinical Dataset for Cardiovascular Health Studies in Mexico
Mariana Avila-Ponce, Sarahi Rodríguez‐González, Eliodoro Castro Montes et al. Lecture notes in networks and systems, 2026. Cites: paper

CardioSight-XAI: Multiclass ECG Beat Classification with Multi-Method Explainable AI for Enhanced Diagnostic Trust
Mubashir Farooq, Asif Ali Banka. Communications in computer and information science, 2026. Cites: paper

Channel Efficiency in ECG-Based Multi-label Cardiac Diagnosis
Dmitry Alexandrov, Claudia Dumitrescu, Sadia Afrin Purba et al. Springer eBooks, 2026. Cites: paper

Classifying Arrhythmia Using Dynamic Mode Decomposition
Shreeshail Bhatta, Dhani Dharmaprani. World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany, 2026. Cites: paper

CNN-FCN-LSTM Based Multimodal Framework for Disease Diagnosis Using Medical Imaging, EHR, and ECG Signals
Shatrunjay Kumar, Devshree Babhale, Vedant Shah et al. Lecture notes in networks and systems, 2026. Cites: paper

Designing a Multimodal Dataset for AI-Based Prognosis in STEMI
Simone Bartucci, Edoardo De Rose, Alessandro Quarta et al. Communications in computer and information science, 2026. Cites: paper

DSTNN-X: ECG Arrhythmia Classification Using Deep Spatio-Temporal Learning with Multi-lead Contextual Aggregation
Yi Xie, Jiepeng Chen, Kai Zheng et al. Lecture notes in networks and systems, 2026. Cites: paper

ECG‐Based Cardiac Arrhythmia Classification Using Coleeg Open‐Source Framework
Mahmoud A. Alnaanah, Mohd H. S. Alrashdan, Hamzah Hmeidi et al. Journal of Electrical and Computer Engineering, 2026. Cites: paper

Enhancing Arrhythmia Classification Through Supervised Clustering in Deep Neural Networks
C. H. Keerthi Vardhan, Methuku Manoj Sai, Peddineni Venkata Sai Rajesh Kumar et al. Lecture notes in networks and systems, 2026. Cites: paper

FedShield: Configurable Mean–Median Robust Aggregation for Poisoning-Resilient Federated Healthcare-IoT Learning
Abdulaziz Saleh Alajaji, Maryam Jamal Alablani, Mohammad Mehedi Hassan. IEEE Access, 2026. Cites: paper

Generalized ECG Heartbeat Classification Using Time-Series Transformers
Timo De Waele, Jaron Fontaine, Eli De Poorter et al. IEEE Access, 2026. Cites: paper

Generation of Realistic Synthetic ECG Data Using Uncertainty-Aware Diffusion Model
Qi Zhang, Hongyan Li. Lecture notes in computer science, 2026. Cites: paper

Heart Rate and Its Variability from Short-Term ECG Recordings as Potential Biomarkers for Classification Using Machine Learning
Vidhi Sutaria, Arpit Jain. Lecture notes in networks and systems, 2026. Cites: paper

Intelligent Monitoring and Analysis System for the Early Detection of Cardiovascular Anomalies Based on IoT and Deep Learning
Dominik Mendoza Ramos, Cristina Vidal Falcon, Abel Rosales Caururu. Communications in computer and information science, 2026. Cites: paper

L2L-ESN: A Lead-to-Lead Electrocardiogram Synthesis Network for Assisting Myocardial Infarction Diagnosis
Jian Tan, Xinrui Qiu, Zhanshuo Shang et al. Intelligent Computing, 2026. Cites: paper

MeDeA: Decomposable Attention for Intrinsically Interpretable ECG Diagnosis
Yulong Ge, Yingying Wang, Qing Ming et al. SSRN Electronic Journal, 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

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

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

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

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