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

AI-Based Early Cardiac Risk Detection and Emergency Alert Using Multi- Parameter Wearable Physiological Monitoring
Sanika Thorat, Sai Bangar, Amaan Inamdar. International Journal of Advanced Research in Science Communication and Technology, 2026. Cites: paper

Continuous multi-step ECG and PPG generation through latent disentanglement
Theekshana Dissanayake, Tharindu Fernando, Simon Denman et al. Computers in Biology and Medicine, 2026. Cites: paper

The Duke Clinically Linked Electrocardiogram and Arrhythmia Repository
Kiran Masroor, Stanton Daries, Ivan Nenadic et al. JACC Advances, 2026. Cites: paper

Контролируемый синтез электрокардиограмм в 12 стандартных отведениях для систем искусственного интеллекта: методологическая модель и требования к валидации
Сергей Анатольевич Атарщиков, Наталья Сергеевна Туманова, Вероника Евгеньевна Вереяскина. Clinical and Fundamental Medicine, 2026. Cites: paper

A Multihead Self-Attention and Adaptive Multiscale Dilated Convolution Model for Generalizable Arrhythmia Classification from ECG Signals
Leihan Gao, 吴植强 WU Zhiqiang, Yuting Li et al. Modelling—International Open Access Journal of Modelling in Engineering Science, 2026. Cites: paper

Repeat variation and definition dependence of ECG/VCG markers: an exploratory audit of one implementation (LoopLens 10.1)
Leo Probst. Research Square, 2026. Cites: dataset

DEFT: Dual-domain multi-resolution fusion transformer for non-stationary medical time series
Lin Guo, Wozhong Chen, Changqing Cheng et al. Information Fusion, 2026. Cites: paper

Physiology-augmented deep representations improve cross-database electrocardiogram beat classification under unseen-domain shift
Mujahid Shahid¹, Oliver Konyo. Research Square, 2026. Cites: paper

Teaching an ECG model where to look does not make it more robust to missing leads: a pre-registered comparison of guideline-based attention guidance with random lead masking
Mohamed Nour Bou Ali, Mohamed Mahmoud. medRxiv, 2026. Cites: dataset, paper

Deep learning-based ECG classification using graph convolutional networks and time-frequency decomposition
Siredj Eddine Benaichouche, Thomas Hilbel, Ailís Ceara Haney et al. Applied Soft Computing, 2026. Cites: paper

Time Reversal Fusion for ECG Reconstruction Before and After Adversarial Fine-Tuning
Jiaqi Liu, Kwok Tai Chui, Lap–Kei Lee et al. Bioengineering, 2026. Cites: paper

Homeostasis-Inspired, Quality-Adaptive Preprocessing for Multi-Label ECG Diagnosis: A Pre-Registered Multi-Objective Evolutionary Study with Negative Findings and Falsifiable Design Principles
Hüseyin Yanık. Biomimetics, 2026. Cites: paper

Improved interpretability and feature attribution for hybrid–AI ECG models by controlling metadata leakage and feature interactions
Lennert Bontinck, Karel Fonteyn, Antônio H. Ribeiro et al. Expert Systems with Applications, 2026. Cites: paper

JEPA-Mamba: a self-supervised joint-embedding architecture with bidirectional Mamba for ECG representation learning
Luyang Dai, Yuwen Li. Biomedical Engineering Letters, 2026. Cites: paper

Diagnostic Preservation After ECG Digitization: From Risk Stratification to Reliability Assurance
Thai Nho Nguyen, Đoàn Văn Thắng. Journal of Trends in Computer Science and Smart Technology, 2026. Cites: paper

Inter-Lead RRI Agreement Between Lead I and Lead II Across Diagnostic ECG Categories: Pilot Evidence for Wearable HRV Monitoring
Naoya Morikawa, Emi Yuda. Applied Sciences, 2026. Cites: paper

A penalized, synergistic deep learning architecture leveraging DBN and GAN for classifying highly asymmetric medical data: A multi-domain validation
Hamidreza Ghasemi, Pedram Salehpour, Fariborz Rahimi. Array, 2026. Cites: paper

Evolution of Automatic Paper Electrocardiogram Digitization: Methods, Applications, and Future Perspectives
Huang Biaosheng, Jincheng Liu, Xueting Tian et al. Electronics, 2026. Cites: paper

Multi-scale temporal feature fusion and lead-graph attention for multi-label classification of 12-lead ECGs
Feiyan Zhou, Mingyang Li. Physiological Measurement, 2026. Cites: dataset, paper

Three-Dimensional Geometric Deformation of the 12-Lead Electrocardiogram in Bundle Branch Block
Patrick Dumitrescu, Igor Antonio Narciso, Johnny Cobas Hernandez et al. Cureus, 2026. Cites: dataset, paper

Quantitative Monitoring of Semantic Regular Expressions with Oracle-Defined Trace Predicates
Matin Amini, Mukund Raghothaman. Lecture notes in computer science, 2026. Cites: dataset

A reproducible benchmark for ECG-to-text report generation: Leakage-safe evaluation, performance floors, and stress testing
Amnon Bleich, Antje Linnemann, B. Diem et al. Biomedical Signal Processing and Control, 2026. Cites: paper

An Adaptive Wavelet–Attention Framework with Dependency-Aware Feature Modeling for Robust ECG Arrhythmia Classification
H. Sumitha, M. Devanathan. Engineering Technology & Applied Science Research, 2026. Cites: paper

Automated Detection of Ventricular Flutter and Ventricular Hypertrophy From ECG Using Deep Learning
Anuradha Pathak, Raghavendra Sharma, Sunil Datt Sharma. Advances in computational intelligence and robotics book series, 2026. Cites: paper

Automated ECG Arrhythmia Detection and Classification Using Deep Convolutional and Residual Neural Networks
Anuradha Pathak, Radhavendra Sharma, Sunil Datt Sharma. Advances in computational intelligence and robotics book series, 2026. Cites: paper

Metaheuristic-Optimized CNN-HRV Fusion for ECG-Based Cardiac Abnormality Risk Detection under Limited Cross-Patient Data
Giovanni Dimas Prenata, Ahmad Ridho’i. Engineering Technology & Applied Science Research, 2026. Cites: paper

A Study on Methods for Evaluating the Quality of Datasets for Intelligent Algorithm Evaluation
Lu Bai, 谷雨晴, Wei Zhang et al. Electronics, 2026. Cites: paper

Lead-aware ECG image representation for Attribute-Invariant cardiomyopathy classification
Bo Chen, Xiazhen Qin, Junjie Cai et al. Pattern Recognition, 2026. Cites: paper

Reconstructive information content of ECG leads and electrodes in premature ventricular contractions: an exhaustive, dual-population study
Fatih KÖKSAL. Journal of Electrocardiology, 2026. Cites: paper

Physio-PPT: Physiology-Anchored Patch-Order Self-supervised Learning for ECG Classification Under Low-Label Regimes
Guilherme A. L. Silva, Pedro H. L. Silva, Arthur Negrão et al. Lecture notes in computer science, 2026. Cites: paper

RELIABILITY-AWARE ARTIFICIAL INTELLIGENCE FOR MULTILABEL ELECTROCARDIOGRAM DIAGNOSIS
Dias Konyspayev, Batyrkhan Kuzenbayev, Nurlybay T. Abatov et al. Scientific Journal of Astana IT University, 2026. Cites: paper

When Not to Diagnose: Evaluating Evidence-Sufficiency Recognition in ECG Multimodal Language Models with ECGTrustBench
Qijia Huang, Jingxia Jiang, Faisal F. Syed et al. International Workshop on Human-Centered Sensing, Modeling, and Intelligent Systems, 2026. Cites: paper

EIA-CKD: An End-to-End Internal Augmentation and Curriculum-based Knowledge Distillation framework for lightweight ECG classification
Nasim Beigzadeh, Mahyar Shahsavari, Abdolhossein Fathi. Biomedical Signal Processing and Control, 2026. Cites: paper

Key Issues in the Processing and Analysis of Large Electrocardiographic Datasets Using Machine Learning Methods
Danylo Zakrzhevsky. Cybernetics and Computer Technologies, 2026. Cites: dataset, paper

MSCA-Mamba: A Compact Multi-Scale Mamba Network for Multi-Label ECG Classification
Dilber Çetintaş. Diagnostics, 2026. Cites: paper

A systematic survey of artificial intelligence methods for ECG-based cardiovascular disease prediction
Thanuja M, Soumyashree M. Panchal, Prasanna Lakshmi G S. Discover Artificial Intelligence, 2026. Cites: paper

Cross-Modal Concept Transfer: From ECG Signals to Images for Explainable Disease Prediction
Chan Lee, Dasom Noh, Minjy Suh et al. Lecture notes in computer science, 2026. Cites: paper

Intelligent Multimodal Biomedical Signal Fusion Using IoT and Deep Learning for Early Disease Prediction
Nadeem Ahmad. International Journal of Scientific Research in Computer Science Engineering and Information Technology, 2026. Cites: paper

Accurate Reconstruction of the Standard 12-Lead ECG from a Single Lead Based on Inherent Principles of ECG
Dong-hyuk Seo, Ui Jong Kim, Yong-Yeon Jo et al. Lecture notes in computer science, 2026. Cites: paper

DFuse: A Dual-Branch Adaptive Fusion Network for Multi-Channel MCG Denoising
Shuai Huang, Hao Li, You Li et al. Lecture notes in computer science, 2026. Cites: paper

ECG-CoCa: Physiology-Informed Contrastive and Generative Framework for ECG Interpretation
Xinyue Liu, Yiming Lei, Shiwei Li et al. Lecture notes in computer science, 2026. Cites: dataset

EmERGE: A Multimodal LLM-Based Evidence-Mediated ECG Report Generation and Evaluation Approach
Keyu Yao, Yuchen Liu, Xiaohan Wang et al. Lecture notes in computer science, 2026. Cites: paper

Inversion from ECG Foundation Model
Junseok Lee, Seungwoo Jung, Gyeongsik Yang et al. Lecture notes in computer science, 2026. Cites: paper

MetaFormer: Efficient Metadata-Guided Transformer for Patient-Aware 12-Lead Electrocardiogram Reconstruction
Yi Xie, Jiepeng Chen, Zefeng Li et al. Lecture notes in computer science, 2026. Cites: paper

MSS-Net: Learning Hierarchical Multi-scale and Multimodal Representations for Complex Cardiac Disease Classification
Yuling Chen, Jiahao Xia, Xingwang Yao et al. Lecture notes in computer science, 2026. Cites: paper

SpikeMamba: Spike-Driven State Space Models for Energy-Efficient Biomedical Sequence Modeling
Si Yong Lee, R V Lee, Hawon Park et al. Lecture notes in computer science, 2026. Cites: paper

A comprehensive survey of machine and deep learning as well as explainable artificial intelligence approaches for heart disease detection
Md. Siam Ansary. Discover Informatics, 2026. Cites: paper

Tri-branch spatio-temporal learning network with dendritic aggregation based dynamic GCN for multi-lead ECG classification
Xulong Kong, Chunyan Ma, Jun Wang et al. Biomedical Signal Processing and Control, 2026. Cites: paper

From twelve leads to single: Cross-lead knowledge distillation for domain-generalized atrial fibrillation detection
Xiaojian Lin, Yang Li, Yaomin Shen et al. Biomedical Signal Processing and Control, 2026. Cites: paper

Enhancing cross-session electrocardiogram biometric authentication with Siamese Autoencoder and phase space features
Wen-Yen Hsu, Shih‐Chin Fang, Hsiao‐Lung Chan. Pattern Recognition Letters, 2026. Cites: paper

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