Publications citing AF Classification from a Short Single Lead ECG Recording: The PhysioNet/Computing in Cardiology Challenge 2017 v1.0.0

Federated Learning for Internet of Medical Things (IoMT): A Secure and Scalable Approach
Ankur Mehra, Gurpreet Singh, Sumit Badotra. International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), 2025. Cites: paper

An Integrated Hidden Markov Model-Van der Pol Oscillator Based Atrial Fibrillation ECG Generator Model
Ayan Mukherjee, Oishee Mazumder, Aniruddha Sinha. European Signal Processing Conference (EUSIPCO), 2025. Cites: paper

Enhanced arrhythmia detection using spiking neural networks: an in-depth analysis of ECG data from the MIMIC-IV clinical database
Gunjan Verma, Honey Gocher, Sweety Verma. Neural Computing and Applications, 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

Detection of Myocardial Infarction Using ECG Signals
Dharshini M, G R Kiranmayi. IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS), 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: paper

Low-Power Flexible Classifier Chip for Atrial Fibrillation Detection
Jose Sanchez, Sumukh Prashant Bhanushali, Sudarsan Sadasivuni et al. IEEE transactions on circuits and systems for artificial intelligence., 2025. Cites: paper

GAEA-Net: Generating Activity-Enriched Abnormal ECGs via Adversarial Network
Liuqing Chen, Shuhong Xiao, Yujie Zang et al. IEEE Journal of Biomedical and Health Informatics, 2025. Cites: paper

The Expanding Landscape of Neural Architectures and Their Impact in Biomedicine
Zijun Frank Zhang, Huixin Zhan, Tinghui Wu et al. Annual Review of Biomedical Data Science, 2025. Cites: paper

Interpretable Deep Learning Models for Arrhythmia Classification Based on ECG Signals Using PTB-X Dataset
Ahmed E. Mansour Atwa, El-Sayed Atlam, Ali Ahmed et al. Diagnostics, 2025. Cites: paper

Automated analysis of ECG signals using nonlinearity and nonstationarity features fed into the MobilenetV2 CNN powered by transfer learning
Richel T. Nguimdo, Alain Tiedeu, Janvier Fotsing. Physical and Engineering Sciences in Medicine, 2025. Cites: paper

Transforming label-efficient decoding of healthcare wearables with self-supervised learning and “embedded” medical domain expertise
Xiao Gu, Zhangdaihong Liu, Jinpei Han et al. Communications Engineering, 2025. Cites: paper

Robust screening of atrial fibrillation with distribution classification
Pierre-François Massiani, Lukas Haverbeck, Claas Thesing et al. Scientific Reports, 2025. Cites: paper

Automated detection of non-physiological artifacts on ECG signal: UK Biobank and CRIC
Syed Hassaan Ahmed Bukhari, Shivangi Kewalramani, Luke Witzigreuter et al. Computers in Biology and Medicine, 2025. Cites: paper

Enhancing Clinical Decision-Making in Rapid Response Systems: Integrating AI-Based Predictions and Early Pattern Clustering
Hyunsun Lim, Kyung Hyun Lee, Jung Hwa Hong et al. Research Square, 2025. Cites: paper

Potential Benefits of Polar Transformation of Time–Frequency Electrocardiogram (ECG) Signals for Evaluation of Cardiac Arrhythmia
Hanbit Kang, Daehyun Kwon, Yoon‐Chul Kim. Applied Sciences, 2025. Cites: paper

SViT-ECG: Spectrogram Vision Transformer for Detection of Short-Term Atrial Fibrillation from ECG Signals
Amir Sorayaie Azar, Jamshid Bagherzadeh, Daniel Teichmann et al. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2025. Cites: paper

Transforming Electrocardiogram to Participant-Level Diagnosis in Atrial Fibrillation Screening*
Zixuan Ding, Jonathan Mant, James David Brimicombe et al. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2025. Cites: paper

Semantic ECG hash similarity graph
Yixian Fang, Shilin Zhang, Yuwei Ren. Scientific Reports, 2025. Cites: paper

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

Augmentation of EEG and ECG Time Series for Machine Learning Applications: Integrating Changepoint Detection into the iAAFT Surrogates
Nina Moutonnet, Gregory Scott, Danilo P. Mandic. International Joint Conference on Neural Networks (IJCNN), 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

An Electrocardiogram Foundation Model Built on over 10 Million Recordings
Jun Li, Aaron D. Aguirre, Valdery F. Moura Junior et al. NEJM AI, 2025. Cites: paper

Optimizing beat-wise input for arrhythmia detection using 1-D convolutional neural networks: A real-world ECG study
Sunghan Lee, Guangyao Zheng, Jeonghwan Koh et al. Computer Methods and Programs in Biomedicine, 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

Improving Atrial Fibrillation Detection with Machine Learning Models
Stojancho Tudjarski, Marjan Gušev, Ana Madevska Bogdanova et al. International Convention on Information and Communication Technology, Electronics and Microelectronics, 2025. Cites: paper

Enhanced ECG Classification using a Hybrid Signal Processing Framework
Bipun Man Pati, Ukesh Thapa, Attaphongse Taparugssanagorn et al. International Symposium on Medical Information and Communication Technology, 2025. Cites: paper

A Comprehensive CNN-LSTMA Model for Cardiovascular Disease Diagnosis
Ch. Mohan Sai Kumar, N. Mouniswar Reddy, M. Lokesh et al. International Conference for Emerging Technology (INCET), 2025. Cites: paper

Time-Series Contrastive Learning Against False Negatives and Class Imbalance
Xiyuan Jin, Jing Wang, Xiaoyu Ou et al. IEEE Transactions on Neural Networks and Learning Systems, 2025. Cites: paper

A Reliable Deep Learning Model for ECG Interpretation: Mitigating Overconfidence and Direct Uncertainty Quantification
Xuedong Li, Qingxiao Zheng, Shibin Zhang et al. Symmetry, 2025. Cites: paper

Multi-Level Explainable AI for ECG-Based Atrial Fibrillation Detection: Exploring LIME, SHAP, and Grad-CAM for Clinical Interpretation
Jake Luo, Amirsajjad Taleban, Patrick Noffke et al. International Conference on Medical and Health Informatics (ICMHI), 2025. Cites: paper

Interpretability of Machine Learning Models for Cardiac Arrhythmia Classification
Bruno Torres Marques, Régis Pires Magalhães, Lívia Almada Cruz et al. Anais do Simpósio Brasileiro de Sistemas de Informação (SBSI), 2025. Cites: paper

Novel ML Algorithms for Healthcare
Mahesh Lokhande, D. S. John Deva Prasanna, P. Selvakumar et al. IGI Global eBooks, 2025. Cites: paper

Energy-Efficient Health Monitoring in Smart Devices: Deep Learning-Based Technique for Wearable ECG Systems
Cong Liu, Jingyang Liu, Dan Wang. IEEE Transactions on Consumer Electronics, 2025. Cites: paper

Prediction of new-onset atrial fibrillation in sepsis patients by machine learning: A systematic review
Shuxuan Ye, Wan Xu, Zhiyu Jiang et al. Digital Health, 2025. Cites: paper

Y-Net-ECG: A Multi-Lead informed and interpretable architecture for ECG segmentation across diverse rhythms
Yuhang Liu, Peng Zhang, Xiaoli Feng et al. Expert Systems with Applications, 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

Resource-Efficient CNN Based Atrial Fibrillation Detection Using P-Wave and RR Interval Features for Edge-AI Cardiac Health Monitoring Devices
Nabasmita Phukan, M. Sabarimalai Manikandan, Ram Bilas Pachori. IEEE Transactions on Artificial Intelligence, 2025. Cites: paper

Detection of Atrial Fibrillation in Holter ECG Recordings by ECHOView Images: A Deep Transfer Learning Study
Vessela Krasteva, Todor Stoyanov, Stefan Naydenov et al. Diagnostics, 2025. Cites: paper

Artificial intelligence in cardiac telemetry
Jiaying Lu, Ran Xiao, Xiao Hu et al. Heart, 2025. Cites: paper

ECG-Based Biometric Recognition: A Survey of Methods and Databases
David Meltzer, David Luengo. Sensors, 2025. Cites: paper

Taming The Overhead of Hiding Samples in Deep Neural Network Training
Truong Thao Nguyen, Edgar Josafat Martinez‐Noriega, Balazs Gerofi et al. 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

Understandable time frame-based biosignal processing
Hamed Rafiei, Mohammad-R. Akbarzadeh-T. Biomedical Signal Processing and Control, 2025. Cites: paper

A knowledge embedded multimodal pseudo-siamese model for atrial fibrillation detection
Chenglin Lin, Huimin Lu, Pengcheng Sang et al. Scientific Reports, 2025. Cites: paper

Application of Deep Learning in ECG Signal Classification: Comparison of CNN, LSTM, and Hybrid Approaches
Muhammad Farid Abidin, Hendra Tjahyadi. International Conference on Computer Sciences, Engineering, and Technology Innovation (ICoCSETI), 2025. Cites: paper

Deep learning for the classification of atrial fibrillation using wavelet transform-based visual images
Ling-Chun Sun, Chia-Chiang Lee, Hung‐Yen Ke et al. BMC Medical Informatics and Decision Making, 2025. Cites: paper

Multiscale feature enhanced gating network for atrial fibrillation detection
Xidong Wu, Mingke Yan, Renqiao Wang et al. Computer Methods and Programs in Biomedicine, 2025. Cites: paper

Automated ECG Analysis with Dual-Channel SqueezeNet Using Hilbert Huang Transform, Fuzzy Entropy, and Hurst Exponent
Richel T. Nguimdo, Alain Tiedeu. Circuits Systems and Signal Processing, 2025. Cites: paper

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