Publications citing Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 v1.0.2

A multi-source domain fine-tuning framework for deep generalization performance in physiological time series analysis
Eran Zvuloni, Guido Gagliardi, Antônio H. Ribeiro et al. Machine Learning Health, 2025. Cites: paper

Can EEG Foundation Models Help with Epileptic Seizure Prediction?
Xudong Guo, L. C. Liu, Sha Lu et al. IEEE International Conference on Big Data (BigData), 2025. Cites: paper

Translation of Radar Signals into Latent Cardiac Event Space for Scalable, Annotation-free Heart Disease Diagnosis
AoXiang Yue, Zhi Peng Lu, Yang Hu et al. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, 2025. Cites: paper

The Evolving Landscape of Artificial Intelligence in Biomedical Imaging
Selahattin Koşunalp, Selma Bulut, Adem Korkmaz. International Conference on Communications, Information, Electronic and Energy Systems (CIEES), 2025. Cites: paper

NERULA: A Dual-Pathway Self-supervised Learning Framework for Electrocardiogram Signal Analysis
Gouthamaan Manimaran, Sadasivan K Puthusserypady, Helena Domínguez et al. Lecture notes in computer science, 2025. Cites: paper

DUDE: deep unsupervised domain adaptation using variable nEighbors for physiological time series analysis
Jeremy Levy, Noam Ben-Moshe, Uri Shalit et al. Physiological Measurement, 2025. Cites: paper

Cardiac Arrhythmia Classification From Lead I ECG Recorded in a Free-Living Environment
Ismail Sadiq, Haneya N. Qureshi, Ali Rizwan et al. IEEE Journal of Biomedical and Health Informatics, 2025. Cites: paper

A Fast, Lightweight, and Generalizable Deep Neural Network for the Detection of Atrial Fibrillation
Harshit Mishra, Farhan Adam Mukadam, Nachiket Makwana et al. medRxiv, 2025. Cites: paper

Explainable ECG Analysis by Explicit Information Disentanglement With VAEs
Viktor van der Valk, Douwe E. Atsma, Roderick W.C. Scherptong et al. IEEE Transactions on Biomedical Engineering, 2025. Cites: paper

Effect Size-Driven Feature Selection and Machine Learning for Interpretable Left Ventricular Hypertrophy Detection from ECG Signals
Gayathiri R R, Arya Bhardwaj, R. Pradeep Kumar et al. IEEE Silchar Subsection Conference (SILCON), 2025. Cites: paper

Timelygpt: extrapolatable transformer pre-training for long-term time-series forecasting in healthcare
Ziyang Song, Qincheng Lu, Hao Xu et al. Health Information Science and Systems, 2025. Cites: paper

Prediction of Atrial Fibrillation From the ECG in the Community Using Deep Learning: A Multinational Study
Luísa Campos Caldeira Brant, Antônio H. Ribeiro, Oseiwe 'Benjamin' B Eromosele et al. Circulation Arrhythmia and Electrophysiology, 2025. Cites: paper

Assessing the Impact of Downsampled ECGs and Alternative Loss Functions in Multi-Label Classification of 12-Lead ECGs
Bjørn-Jostein Singstad, Eraraya Morenzo Muten. Cardiovascular Engineering and Technology, 2025. Cites: paper

Interpretable Classification of Cardiac Arrhythmias Using Reduced ECG Leads With CNNs
Karla Ruíz, Didier Moreno, Harold H. Rodriguez et al. IEEE Colombian Caribbean Conference (C3), 2025. Cites: paper

The CAPSARII Approach to Cyber-Secure Wearable, Ultra-Low-Power Networked Sensors for Soldier Health Monitoring
Luciano Bozzi, Christian Celidonio, Umberto Nuzzi et al. Euromicro Conference on Digital System Design (DSD), 2025. Cites: paper

ECG classification with convolutional neural networks demonstrates resilience to sex-imbalances in data
Diantha J. M. Schipaanboord, Floor B.H. van der Zalm, René van Es et al. medRxiv, 2025. Cites: paper

Fusion of automatically learned rhythm and morphology features matches diagnostic criteria and enhances AI explainability
Alexander Hammer, Marc Goettling, Hagen Malberg et al. npj Artificial Intelligence, 2025. Cites: dataset, paper

Reducing leads, enhancing wearable practicality: A comparative study of 3-lead vs. 12-lead ECG classification
Sergio González-Cabeza, Mario Sanz-Guerrero, Luís Piñuel et al. Medical Engineering & Physics, 2025. Cites: paper

Lead Analysis for the Classification of Multi-Label Cardiovascular Diseases and Neural Network Architecture Design
Tao Yang, Chao-Xin Xie, Hui-Ming Huang et al. Electronics, 2025. Cites: paper

The Multi-Branch Deep-Learning-Based Approach to Heart Dysfunction Classification
Krzysztof Hryniów, Bartosz Puszkarski, Marcin Iwanowski C. Applied Sciences, 2025. Cites: paper

Transparent and Robust Artificial Intelligence-Driven Electrocardiogram Model for Left Ventricular Systolic Dysfunction
Min Sung Lee, Jong-Hwan Jang, Sora Kang et al. Diagnostics, 2025. Cites: paper

An early warning method for arrhythmias in long-term ECGs based on self-supervised learning and LSTM
Zhiyuan Li, Yuanyuan Tian, Yanrui Jin et al. Knowledge-Based Systems, 2025. Cites: paper

A Comparative Analysis of Centralized and Federated Learning for Multimodal ECG and PCG Classification
Martim G. Silva, Bruno Oliveira, Miguel Tavares Coimbra et al. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2025. Cites: paper

Cardi-GPT v2: An Adaptive Expert ECG-Record Processing Chatbot
Koustav Mallick, Neel Singh, Mohammadreza Hajiarbabi. International Conference on Data Intelligence and Cognitive Informatics (ICDICI), 2025. Cites: paper

Atrial Fibrillation and Atrial Flutter Detection Using Deep Learning
Dimitri Kraft, Peter Rumm. Sensors, 2025. Cites: paper

Fulcrum Rebalancing and Hybrid Classification for Multi-Class Multi-Labeled ECG
Ayan Mukherjee, Varsha Sharma, Anirban Dutta Choudhury et al. International Joint Conference on Neural Networks (IJCNN), 2025. Cites: paper

A survey of transformers and large language models for ECG diagnosis: advances, challenges, and future directions
Mohammed Yusuf Ansari, Mohammed Yaqoob, Mohammed Ishaq et al. Artificial Intelligence Review, 2025. Cites: paper

Atrial Fibrillation Signal Generation Based on 2D Image Generation Model
Zhihong Chen, Yonghong Xu. Circuits Systems and Signal Processing, 2025. Cites: paper

An Artificial Intelligence QRS Detection Algorithm for Wearable Electrocardiogram Devices
Zihao Li, Wenliang Zhu, Yiheng Xu et al. Micromachines, 2025. Cites: paper

Transfer learning in ECG diagnosis: Is it effective?
Cuong V. Nguyen, Cuong Do. PLoS ONE, 2025. Cites: paper

Compression Meets Security: Low-Complexity Linear Collaborative Federated Learning With Enhanced Accuracy
Tianshun Wang, Peichun Li, Panpan Feng et al. IEEE Transactions on Mobile Computing, 2025. Cites: paper

Cardiovascular Risk Assessment via Sleep Patterns and ECG-Based Biological Age Estimation
Gouthamaan Manimaran, Sadasivan K Puthusserypady, Helena Domínguez et al. Journal of Clinical Medicine, 2025. Cites: paper

Multi-source ECG Signal-Based Cardiac-Abnormality Pattern Classification with Fast–Slow Learning DNNs
Sandhya Samant, Dev Baloni. Journal of The Institution of Engineers (India) Series B, 2025. Cites: paper

Poincaré Image Analysis of Short-Term Electrocardiogram for Detecting Atrial Fibrillation
Md Mayenul Islam, Mohammod Abdul Motin, Sumaiya Kabir et al. IEEE Journal of Biomedical and Health Informatics, 2025. Cites: paper

Cross-device federated unsupervised learning for the detection of anomalies in single-lead electrocardiogram signals
Maximilian Kapsecker, Stephan Jonas. PLOS Digital Health, 2025. Cites: paper

Cardi-GPT: An Expert ECG-Record Processing Chatbot
Koustav Mallick, Neel Singh, Mohammedreza Hajiarbabi. IEEE SoutheastCon, 2025. Cites: paper

Hybrid Feature Extraction for 12-Lead Ecg Classification by Integrating Handcrafted and Deep Learning Techniques
Oleksandr Ponemash, A. A. M. Muzahid, Reda Lamtoueh et al. International Conference on Computer and Automation Engineering, 2025. Cites: paper

Privacy-preserving Framework for Automated Detection of Arrhythmia in ECG Data
Kacper Gil, Andrés Véjar. Journal of Telecommunications and Information Technology, 2025. Cites: paper

Semi-supervised multi-label cardiovascular diseases detection via contrastive learning and label inference
Ning Wang, Haiyan Wang, Panpan Feng et al. Knowledge-Based Systems, 2025. Cites: paper

A data-augmented vision transformer model for robust multi-label ECG arrhythmia classification
Aymen Abid, Omar Cheikhrouhou. International Journal of Information Technology, 2025. Cites: paper

Towards Transparent AI in Medicine: ECG-Based Arrhythmia Detection with Explainable Deep Learning
Oleksii Kovalchuk, Olexander Barmak, Pavlo Radiuk et al. Technologies, 2025. Cites: paper

A Review of Deep Learning for Biomedical Signals: Current Applications, Advancements, Future Prospects, Interpretation, and Challenges
Ali Mohammad Alqudah, Zahra Moussavi. Computers, materials & continua/Computers, materials & continua (Print), 2025. Cites: paper

Integrating deep learning with ECG, heart rate variability and demographic data for improved detection of atrial fibrillation
Araz Rawshani, Aidin Rawshani, Gustav Jan Smith et al. Open Heart, 2025. Cites: paper

Securing Deep Learning Models with Differential Privacy for Cardiovascular Disease Prediction
Zoher Orabe, Antti Vasankari, Tapio Pahikkala et al. SSRN Electronic Journal, 2025. Cites: paper

Wrist-Worn Devices for Remote Monitoring of Cardiovascular Disease: A Survey
Ismail Sadiq, Aneeqa Ijaz, Ali Imran. IEEE Access, 2025. Cites: paper

CORKI: A Correlation-Driven Imputation Method for Partial Annotation Scenarios in Multi-label Clinical Problems
Ricardo Santos, Bruno Ribeiro, Isabel Curioso et al. Communications in computer and information science, 2024. Cites: paper

Advanced Deep Neural Network with Unified Feature-Aware and Label Embedding for Multi-Label Arrhythmias Classification
Pan Xia, Zhongrui Bai, Yicheng Yao et al. Tsinghua Science & Technology, 2024. Cites: paper

ECG-LLM: Leveraging Large Language Models for Low-Quality ECG Signal Restoration
Longfei Liu, Guosheng Cui, Cheng Wan et al. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2024. Cites: paper

Foundation model of ECG diagnosis: Diagnostics and explanations of any form and rhythm on ECG
Yuanyuan Tian, Zhiyuan Li, Yanrui Jin et al. Cell Reports Medicine, 2024. Cites: paper

An ECG-Based Model for Left Ventricular Hypertrophy Detection: A Machine Learning Approach
Marion Taconné, Valentina Corino, Luca Tommaso Mainardi. IEEE Open Journal of Engineering in Medicine and Biology, 2024. Cites: paper

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