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

Synthesis of Standard 12-Lead ECG from Single-Lead ECG Using Shifted Diffusion Models
Jingwei Liu, Hongyan Li, Shenda Hong. Lecture notes in computer science, 2024. Cites: paper

The Fusion Model of ResNet and GRU Based on Simplified Self-Attention for ECG Classification on PTB-XL Dataset
Zicong Yang, Aitong Jin, Yan Liu et al. Studies in computational intelligence, 2024. Cites: paper

Toward Robust Automated Cardiovascular Arrhythmia Detection using Self-supervised Learning and 1-Dimensional Vision Transformers
Mitchell John Violini Chatterjee. 2024. Cites: paper

Towards Trustworthy AI in Cardiology: A Comparative Analysis of Explainable AI Methods for Electrocardiogram Interpretation
Nils Gumpfer, Borislav Dinov, Samuel Tobias Sossalla et al. Lecture notes in computer science, 2024. Cites: paper

Toward Trustworthiness of Deep Learning Models for 12-Lead ECGs
Theresa Bender. 2024. Cites: paper

CureNet: Improving Explainability of AI Diagnosis Using Custom Large Language Models
Subhash Khambampati, Sushanth Dondapati, Tejo Vardhan Kattamuri et al. International Conference on Smart Generation Computing, Communication and Networking (SMART GENCON), 2023. Cites: paper

Pre-Processing techniques and artificial intelligence algorithms for electrocardiogram (ECG) signals analysis: A comprehensive review
Muhammad Farhan Safdar, Robert Marek Nowak, Piotr Pałka. Computers in Biology and Medicine, 2023. Cites: paper

Analyse avancée de signaux ECG acquis en IRM
Pierre Gabriel Aublin. 2023. Cites: paper

Automatic analysis of cardiac function with artificial intelligence : multimodal approach for portable echocardiographic devices
Yingyu Yang. 2023. Cites: paper

DDDG: A dual bi-directional knowledge distillation method with generative self-supervised pre-training and its hardware implementation on SoC for ECG
Huaicheng Zhang, Wenhan Liu, Qianxi Guo et al. Expert Systems with Applications, 2023. Cites: paper

Energy Efficient ECG Classifier Using Smart Lead Switching and Apache TVM
Ahmad Ayad, Mahdi Barhoush, Benedikt Völker et al. International Conference on Machine Learning and Applications, 2023. Cites: paper

Semi-Supervised Learning for Multi-Label Cardiovascular Diseases Prediction: A Multi-Dataset Study
Rushuang Zhou, Lei Lü, Zijun Liu et al. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023. Cites: paper

Diagnosis of atrial fibrillation based on AI-detected anomalies of ECG segments
Sanghoon Choi, Kyung Min Choi, Hong Kyun Yun et al. Heliyon, 2023. Cites: paper

CardioDiverse: A Balanced ECG Dataset for Improved Association of Heart Diseases with Relevant Leads
Ahmad Mousa, Khalid Elgazzar. IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT), 2023. Cites: paper

Towards explaining deep neural network-based heart age estimation
Philip Hempel, Theresa Bender, Keshav Gandhi et al. IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, 2023. Cites: paper

Lightweight Lossy/Lossless ECG Compression for Medical IoT Systems
Yangyang Chang, Gerald E. Sobelman. IEEE Internet of Things Journal, 2023. Cites: paper

Classification of Abnormal Cardiac Rhythm from Brief Single-Lead ECG Recordings using Embeddings from Transformer Encoder Models
B.S. Utkars Jain, Prahlad G. Menon. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2023. Cites: paper

Energy Efficient AI/ML based Continuous Monitoring at the Edge: ECG and EEG Case Study
Umair Mohammad, Fahad Saeed. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2023. Cites: paper

Self-supervised learning for atrial fibrillation detection with ECG using CNNTransformer
Congyu Zou, Alexander Müller, Eimo Martens et al. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2023. Cites: paper

Detecting Data Poisoning in Split Learning Using Intraclass- Distance Inflated Loss
Mohammad Kohankhaki, Ahmad Ayad, Mahdi Barhoush et al. IEEE Globecom Workshops (GC Wkshps), 2023. Cites: paper

A lightweight SelfONN model for general ECG classification with pretraining
Keke Qin, Wu Xin Huang, Tao Zhang et al. Biomedical Signal Processing and Control, 2023. Cites: paper

Model for classification of heart failure severity in patients with hypertrophic cardiomyopathy using a deep neural network algorithm with a 12-lead electrocardiogram
Sanshiro Togo, Yuki Sugiura, Sayumi Suzuki et al. Open Heart, 2023. Cites: paper

Interpretability of Neural Networks applied to Electrocardiograms : Translational Applications in Cardiovascular Diseases
Ahmad Fall. 2023. Cites: paper

SIGxCL: A Signal–Image–Graph Cross-Modal Contrastive Learning Framework for CVD Diagnosis Based on Internet of Medical Things
Huaicheng Zhang, Wenhan Liu, Zhoutong Li et al. IEEE Internet of Things Journal, 2023. Cites: paper

Influence of the Training Set Composition on the Estimation Performance of Linear ECG-Lead Transformations
Daniel Guldenring, Dewar Finlay, Raymond Bond et al. Computing in cardiology, 2023. Cites: paper

Spectral Cross-Domain Neural Network With Soft-Adaptive Threshold Spectral Enhancement
Che Liu, Sibo Lucas Cheng, Weiping Ding et al. IEEE Transactions on Neural Networks and Learning Systems, 2023. Cites: paper

AttentionCovidNet: Efficient ECG-based diagnosis of COVID-19
Wesley Chorney, Haifeng Wang, Lir‐Wan Fan. Computers in Biology and Medicine, 2023. Cites: paper

AI-Based Detection of Myocardial Infarction through Electrocardiogram Signals: A Review
Yasmine Shabaan, Naglaa Fathy, Tamer A. Mostafa et al. International Conference on Intelligent Computing and Information Systems (ICICIS), 2023. Cites: paper

PEACE: Private and Energy-Efficient Algorithm for Cardiac Evaluation on the EDGE using Modified Split Learning and Model Quantization
Ahmad Ayad, Mahdi Barhoush, Johnson Loh et al. International Conference on Information and Communication Systems (ICICS), 2023. Cites: paper

TT-DCWN: A Two-Task Branch Densely Connected Weight Network for Myocardial Infarction Detection and Location Using 12-Lead Raw Electrocardiograms
Yupeng Qiang, Xunde Dong, Yang Yang. China Automation Congress (CAC), 2023. Cites: paper

DAMS-Net: Dual attention and multi-scale information fusion network for 12-lead ECG classification
Rongzhou Zhou, Junfeng Yao, Qingqi Hong et al. Methods, 2023. Cites: paper

In-Distribution and Out-of-Distribution Self-Supervised ECG Representation Learning for Arrhythmia Detection
Sahar Soltanieh, Javad Hashemi, Ali Etemad. IEEE Journal of Biomedical and Health Informatics, 2023. Cites: paper

A More Secure Split: Enhancing the Security of Privacy-Preserving Split Learning
Tanveer Khan, Khoa Nguyen, Antonis Michalas. Lecture notes in computer science, 2023. Cites: paper

Exploring CNN and XAI-based Approaches for Accountable MI Detection in the Context of IoT-enabled Emergency Communication Systems
Helene Knof, Prachi Bagave, Michell Boerger et al. International Conference on the Internet of Things (IoT), 2023. Cites: paper

SRTNet: Scanning, Reading, and Thinking Network for myocardial infarction detection and localization
Kaige Liu, Tong Liu, Dunwei Wen et al. Expert Systems with Applications, 2023. Cites: paper

IoT System and Deep Learning Model to Predict Cardiovascular Disease Based on ECG Signal
Nizar Sakli, Chokri Baccouch, Hédia Bellali et al. Advances in Science Technology and Engineering Systems Journal, 2023. Cites: paper

A CNN based multifaceted signal processing framework for heart rate proctoring using Millimeter wave radar ballistocardiography
Rafid Umayer Murshed, Md. Abrar Istiak, Md. Toufiqur Rahman et al. Array, 2023. Cites: paper

ST-ReGE: A Novel Spatial-Temporal Residual Graph Convolutional Network for CVD
Huaicheng Zhang, Wenhan Liu, Sheng Chang et al. IEEE Journal of Biomedical and Health Informatics, 2023. Cites: paper

Explainable Deep Learning Based-System for Multilabel Classification of 12-Lead ECG
Yousra Chahinez Hadj Azzem, Fouzi Harrag. International Conference on Networking and Advanced Systems (ICNAS), 2023. Cites: paper

MSFNet: Multi-Stage Fusion Network for Myocardial Infarction Classification
Luming Zhang, Xuesong Su, Wenguang Zheng. International Conference on Computer Engineering and Intelligent Control (ICCEIC), 2023. Cites: paper

Applying Generative Models and Transfer Learning to Physiological Data Classification
José Fernando Núñez, Jamie Arjona, Adrián Tormos et al. Frontiers in artificial intelligence and applications, 2023. Cites: paper

Artificial Intelligence in Medicine: The Influence of Medical Expertise and Perceived Causability on Medical AI Risk and Benefit Perception
Nadia Said, Lea Schumacher, Markus Huff. 2023. Cites: paper

IRIDIA-AF, a large paroxysmal atrial fibrillation long-term electrocardiogram monitoring database
Cédric Gilon, Jean-Marie Grégoire, Marianne Mathieu et al. Scientific Data, 2023. Cites: paper

Privacy Preserving Heart Rate Estimation from ECG and PPG Signals for Application in Remote Healthcare
Tasnim Nishat Islam, Hafiz Imtiaz. Research Square, 2023. Cites: paper

Selective Lead Integration: Enhancing ECG Classification for Effective Cardiac Monitoring
Ahmad Mousa, Khalid Elgazzar. IEEE World Forum on Internet of Things (WF-IoT), 2023. Cites: paper

Multi-scale SE-residual network with transformer encoder for myocardial infarction classification
Qingyu Yao, Luming Zhang, Wenguang Zheng et al. Applied Soft Computing, 2023. Cites: paper

ECG Synthesis via Diffusion-Based State Space Augmented Transformer
Md Haider Zama, Friedhelm Schwenker. Sensors, 2023. Cites: paper

A lightweight U-Net model for denoising and noise localization of ECG signals
Lei Hu, Wenjie Cai, Ziyang Chen et al. Biomedical Signal Processing and Control, 2023. Cites: paper

CardiAWARE: A Novel ECG-based Deep Neural Network Algorithm for Early Detection of Cardiac Conditions
Eashan Kosaraju. IEEE MIT Undergraduate Research Technology Conference (URTC), 2023. Cites: paper

Predictive maintenance of aircraft bleed air systems : an approach based on machine learning and variational autoencoders
William Todo. 2023. Cites: paper

Cited by