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

Atrial Fibrillation and Sinus Rhythm Detection Using TinyML (Embedded Machine Learning)
Gislayne Rocha dos Santos Silva, M. D. B. Lima, José Alberto Ferreira Filho et al. World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany, 2024. Cites: paper

Attention-assisted hybrid CNN-BILSTM-BiGRU model with SMOTE–Tomek method to detect cardiac arrhythmia based on 12 - lead electrocardiogram signals
Sara Chopannejad, Arash Roshanpoor, Farahnaz Sadoughi. Digital Health, 2024. Cites: paper

Attention-Based Convolutional Neural Network for Imbalanced Multi-Label Electrocardiogram
诗雨张. Modeling and Simulation, 2024. Cites: paper

BioU-Net: Diagnosis Network Based on Spectral Feature Enhancement for Myocardial Infarction
Siyuan Li, Wenguang Zheng, Jiayang Li et al. Lecture notes in computer science, 2024. Cites: dataset

Breaking Boundaries in Diagnosis: Non-Invasive Anemia Detection Empowered by AI
Muljono Muljono, Sari Ayu Wulandari, Harun Al Azies et al. IEEE Access, 2024. Cites: paper

Computational modeling for medical data: From data collection to knowledge discovery
Yang Yin, Shuangbin Xu, Yifan Hong et al. The Innovation Life, 2024. Cites: paper

DeepAF: A Multi-task Deep Learning Model for Arrhythmias Detection at Resource-Constrained Mobile Device
Fotsing Kuetche, Noura Alexendre, Ntsama Eloundou Pascal et al. Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2024. Cites: dataset

Deep Learning-Based Ensemble Model for Detection of Myocardial Infarction from ECG Data
Dipanwita Saha, Nitu Saha, Gunjan Mukherjee et al. Lecture notes in networks and systems, 2024. Cites: paper

Deep machine learning for biosignal analysis
Pubudu Theekshana Thilakasiri Dissanayakage. Queensland University of Technology, 2024. Cites: paper

Design of an Integrated Myocardial Infarction Detection Model Using ECG Connectivity Features and Multivariate Time Series Classification
Pushpam Jain, Amey Deshmukh, Himanshu Pramod Padole. IEEE Access, 2024. Cites: paper

Development of a Bagging-based Ensemble Model for ECG Classification
Ballali Ebbi, Hammada. University Of Wales Trinity Saint David Research Repository (University of Wales Trinity Saint David), 2024. Cites: paper

ECG Based Heart Disease Classification: Advancement and Review of Techniques
Akshita Gour, Muktesh Gupta, Rajesh Wadhvani et al. Procedia Computer Science, 2024. Cites: paper

ECG Signals Classification by Analyzing Label Correlation Based on Deep Learning
诗雨张. Modeling and Simulation, 2024. Cites: paper

Enhanced 12-Lead ECG Reconstruction from Single-Lead Data Using WaveNet
Jamal Et-Tousy, Et-Tousy Said, Soufiane Ait El Aouad et al. ITM Web of Conferences, 2024. Cites: paper

Explainable Rhythm-Based Heart Disease Detection from ECG Signals
Dereje Degeffa Demissie, Fitsum Assamnew Andargie. Communications in computer and information science, 2024. Cites: paper

Explanations of Augmentation Methods for Deep Learning ECG Classification
Nikil Sharan Prabahar Balasubramanian, Sagnik Dakshit. Lecture notes in computer science, 2024. Cites: paper

iCardo 3.0: A Machine Learning Framework for Prediction of Conduction Disturbance in Heart
Nidhi Sinha, Amit M. Joshi, Saraju P. Mohanty. Lecture notes in networks and systems, 2024. Cites: paper

Isolation of ECG Sections Associated with Signs of Cardiovascular Diseases Using the Transformer Architecture
Alexey Petukhov, Denis Rodionov, Denis Karchkov et al. Communications in computer and information science, 2024. Cites: dataset, paper

KUMA-MI: A 12-Lead Knowledge-Guided Multi-branch Attention Networks for Myocardial Infarction Localization
Jun Long, Jichao Yang, Lin Guo et al. Lecture notes in computer science, 2024. Cites: paper

Learning Representations for Multilead Electrocardiograms From Morphology-Rhythm Contrast
Wenhan Liu, Huaicheng Zhang, Sheng Chang et al. IEEE Transactions on Instrumentation and Measurement, 2024. Cites: paper

Leveraging Temporal Patterns: Automated Augmentation to Create Temporal Early Exit Networks for Efficient Edge AI
Max Sponner, Lorenzo Servadei, Bernd Waschneck et al. IEEE Access, 2024. Cites: paper

Machine learning models to help classification of cardiovascular disease
Khaoula Oueldji, Nadir Farah. Advances in intelligent systems research/Advances in Intelligent Systems Research, 2024. Cites: paper

MEDBind: Unifying Language and Multimodal Medical Data Embeddings
Yuan Gao, Sangwook Kim, David E. Austin et al. Lecture notes in computer science, 2024. Cites: paper

Morphology-Aware ECG Diagnostic Framework With Cross-Task Attention Transfer for Improved Myocardial Infarction Diagnosis
Pharvesh Salman Choudhary, Samarendra Dandapat. IEEE Transactions on Instrumentation and Measurement, 2024. Cites: paper

Multi-Label Imbalanced ECG Signal Classification Based on Deep Learning
浩丞顾. Modeling and Simulation, 2024. Cites: paper

Online Co-Learning Strategy Based on Multibranch Multiscale Network for 12-Lead ECG Classification
Shuze Han, Caiyun Ma, Z. J. Wang et al. IEEE Transactions on Instrumentation and Measurement, 2024. Cites: paper

Physiological and Inertial Features based Dataset for Falls and Activities: PIF v2
Rajbinder Kaur, Rohini Sharma, Manpreet Kaur Dhaliwal. Procedia Computer Science, 2024. Cites: paper

Quantitative Evaluation of xAI Methods for Multivariate Time Series - A Case Study for a CNN-Based MI Detection Model
Helene Knof, Michell Boerger, Nikolay Tcholtchev. Communications in computer and information science, 2024. Cites: paper

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. Carleton University's Institutional Repository (MacOdrum Library, Carleton University), 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. eDiss (Georg-August-Universität Göttingen), 2024. Cites: paper

Застосування сіамських нейронних мереж для підвищення точності виявлення серцево-судинних захворювань за нестачі тренувальних даних
Anton Volodymyrovych Mnevets, Н. Г. Иванушкина, K.O. Ivanko. eNTUKhPIIR Repository (Kharkiv Polytechnic Institute), 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. theses.fr (ABES), 2023. Cites: paper

Automatic analysis of cardiac function with artificial intelligence : multimodal approach for portable echocardiographic devices
Yingyu Yang. theses.fr (ABES), 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

Cited by