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

Computer-Aided-Diagnosis of Cardiac Arrhythmia Using a Three-Channel Convolutional Neural Network
Richel T. Nguimdo, Alain Tiedeu, Janvier Fotsing et al. IntechOpen eBooks, 2026. Cites: paper

Hybrid System for Smart Healthcare Monitoring Using AI and IoT
Sakshi Dhumone, Supriya Narad. Lecture notes in networks and systems, 2026. Cites: paper

Leveraging the wearable 1-lead ECG signal. From cardiac rhythm to cardiac function assessment
Viktor van der Valk, Douwe E. Atsma, Roderick Scherptong et al. npj Cardiovascular Health, 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

Lightweight Deep Learning for Atrial Fibrillation Detection from Single-Lead Wearable ECG: A Benchmark of Convolutional, Temporal, and Mamba-Inspired Architectures
Hamim Islam Hellol, Md Al Ridwan, Md Shahnawaj et al. BioMedInformatics, 2026. Cites: paper

Beyond full fine-tuning: towards enhanced generalizability in downstream ECG foundation model adaptation
Giuliana Monachino, Beatrice Zanchi, Georgiy Farina et al. Scientific Reports, 2026. Cites: paper

Early Detection of Multi-class Arrhythmia in ECG: Use of Mamba for Edge Devices in MedTech
Prashant Bharti, Utkarsh Rana, Jignesh S. Bhatt. Lecture notes in computer science, 2026. Cites: paper

Cardiovascular Disease Prediction Using Multimodal
B. Yugandran, Vishal Surya Thanjavur, M. Vaidhehi. Lecture notes in networks and systems, 2026. Cites: paper

AI-Enabled Atrial Fibrillation Detection, Prediction, and Classification Based on ECG Data: A Review
Kimia Tahvildari, Fatih Kahraman. Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 2026. Cites: paper

From Prediction to Confidence: A Survey of AI-Based ECG Uncertainty Quantification Methods
Ibrahima Sy, Ndeye Fatou Ngom, Cheikh H. T. C. Ndiaye. Lecture notes in networks and systems, 2026. Cites: paper

Forecasting 1-year atrial fibrillation risk from sinus rhythm electrocardiograms in arrhythmia-naïve patients
Nathan T. Riek, Tanmay Gokhale, Rui Qi Ji et al. Heart Rhythm O2, 2026. Cites: paper

Lightweight and Interpretable LSVM for Multi-Class ECG Arrhythmia Classification Using Multi-Database PhysioNet Signals
Syed Muhammad Abdul Rehman, Nadeem Ahmad Khan, Muhammad Awais Bin Altaf. IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), 2026. Cites: paper

A meta-learning method with reduced data requirements for training and updating deep learning models on wearable devices
Alireza Amirshahi, Maedeh H. Toosi, Siamak Mohammadi et al. Communications Medicine, 2026. Cites: paper

A lightweight hybrid framework integrating convolutional neural networks and fast Fourier transform for reliable and calibrated ECG-based cardiac abnormality detection
Abdoul Malik, Selim Aras. PLoS ONE, 2026. Cites: paper

Desenvolvimento de Firmware para Detecção de Anomalias no ECG em Monitor Multiparâmetros
Claudinei Pereira de Moraes, Fábio Iaione, Luiz Eduardo Schardong Spalding. 2026. Cites: paper

A systematic review of ECG arrhythmia classification: embedded feasibility, adherence to standards, and fair evaluation
Guilherme A. L. Silva, Pedro H. L. Silva, Gladston J. P. Moreira et al. Research on Biomedical Engineering, 2026. Cites: paper

AF-EMFM: Multi-Modal Feature Fusion with Enhanced Multi-Scale Module for Atrial Fibrillation Classification
Yang Chen, Pengjia Qi, Jijun Tong. Lecture notes in computer science, 2026. Cites: paper

Deep learning for heart disease anomaly detection: performance factors and algorithms
Hong Zhou, Duc-Anh Nguyen, Nhien‐An Le‐Khac. Artificial Intelligence Review, 2026. Cites: paper

ECG-image-database: large-scale paired ECG images and time-series with real-world artifacts; a foundation for computerized ECG digitization and analysis
Matthew A. Reyna, Deepanshi Deepanshi, James Tyler Weigle et al. Physiological Measurement, 2026. Cites: paper

A Sensing Platform for Personal Comfort Model Development and Application Based on Wearable and Environmental Sensors
Dianel Ago, Gloria Cosoli, Silvia Angela Mansi et al. IEEE International Workshop on Metrology for Living Environment (MetroLivEnv), 2026. Cites: paper

Low-Complexity Dual-Path Cross-Attention Fusion Model for Real-Time Atrial Fibrillation Recognition
Oscal Tzyh-Chiang Chen, Guan-Ming Huang, Guo-Zua Wu. International Conference on Advanced Machine Learning and Data Science (AMLDS), 2026. Cites: paper

Spatio-Temporal Feature Fusion via Lightweight Hybrid CNN-Transformers for Atrial Fibrillation Detection
Thi Minh Tuyen Huynh, Thi Viet Ha Nguyen, Huu-Thuan Huynh et al. International Conference on Communications and Electronics (ICCE), 2026. Cites: paper

Single-Lead ECG Arrhythmia Classification Based on Peak-Enhanced Attention Network and Quality-Aware GAN Data Augmentation Framework
Yaoyu Zhang, Yi Xia. Sensors, 2026. Cites: paper

Site-Aware Federated Learning via Embedding and Resampling with Electrocardiograms
Wesley Chorney, Sing Hui Ling, Haifeng Wang. Information, 2026. Cites: paper

Toward personalised cancer care: AI in precision and molecular oncology
Abhishek Sinha, Danyaal Anzar, Akosua Bempomaa Owusu-Boampong et al. European journal of medical research, 2026. Cites: paper

Energy-Efficient Atrial Fibrillation Detection From Compressive Sensing-Based ECG Using a Lightweight CNN–BiLSTM Model for Resource-Constrained Wearable Health Monitoring Systems
Sajeev K. Jose, Narendra Kumar Reddy Gangireddy. IEEE Sensors Journal, 2026. Cites: paper

A Comprehensive Review of Ultra-Low Power Fpga-Based Architectures for Edge Ai in Wearable Health Monitoring Systems
Promila, Meenakshi Aggarwal. IEEE Global Symposium on Emerging and Communication Technologies (GSEACT), 2026. Cites: paper

DeepECG-Kit: A Practical and Reproducible Framework for ECG Deep Learning
Steven Hicks, Mary M. Maleckar, Thomas Dreibholz et al. IEEE International Symposium on Computer-Based Medical Systems (CBMS), 2026. Cites: paper

A lightweight and robust parallel CNN–LSTM network with random crop augmentation for single-lead raw ECG arrhythmia classification
Emir Ali Dinsel, Halife Kodaz. Engineering Science and Technology an International Journal, 2026. Cites: paper

Federated Few-Shot Learning for Internet of Medical Things Applications: Towards Effective AFib Detection
Shahid Latif, Djamel Djenouri, Jawad Elsayed Ahmad. International Conference on Communications, 2026. Cites: paper

Beyond the black box: interpretability, accountability, and responsible clinical integration of AI-driven heart rate variability models—a narrative review
Alexandru Burlacu, Maria Olariu, Oana Geman et al. Frontiers in Computer Science, 2026. Cites: paper

Advances in artificial intelligence techniques for diagnosis of cardiac diseases
Essam Halim Houssein, Hebatollah Mostafa, Abdelmgeid Amin Ali et al. Discover Artificial Intelligence, 2026. Cites: paper

RT-AFNet: A Hybrid ResNet-Transformer Architecture with Multi-Scale Fusion for Atrial Fibrillation Detection
Xinyu Hu, Qingqing Duan, Yuwei Zhang et al. Biosensors, 2026. Cites: paper

A Deep Neural Network for Interpreting Wearable Electrocardiogram Data in Atrial Fibrillation: Prospective Observational Diagnostic Accuracy Study
Olli Rantula, Jukka A. Lipponen, Jari Halonen et al. JMIR mhealth and uhealth, 2026. Cites: paper

CoFE: A Framework Generating Counterfactual ECG for Explainable Cardiac AI-Diagnostics
Jong-Hwan Jang, Junho Song, Yong‐Yeon Jo. IEEE International Conference on Acoustics Speech and Signal Processing, 2026. Cites: paper

Cross-Modality Self-Supervision for Unimodal Physiological Signals Representation Learning
Xiaomao Fan, Shuangdu Li, Jikui Liu et al. IEEE International Conference on Acoustics Speech and Signal Processing, 2026. Cites: paper

MDF: A Model Dispatching Framework with Noise-Estimator-Centric Experts for Robust Biosignal Classification
Zhengyang Miao, Xidong Wu, Liping Xie. IEEE International Conference on Acoustics Speech and Signal Processing, 2026. Cites: paper

Azure-Based Healthcare Risk Analytics with Machine Learning and Power BI
N. Saikiran, Govindu Dharani, S Akash Naik et al. International Conference on Artificial Intelligence and Machine Learning Applications Theme: Healthcare and Internet of Things (AIMLA), 2026. Cites: paper

Программно-аппаратный исследовательский комплекс диагностики состояния человека на основе облачной микросервисной архитектуры
Nedyalko Borisov, Denis Karchkov, Galina Kuzenkova. Sovremennye informacionnye tehnologii i IT-obrazovanie., 2026. Cites: paper

Mamba: Efficient State-Space Modeling for Short-Window Atrial Fibrillation Detection from 12-Lead ECG
Mecheri Metidji, Abdou El Karim Tahari, Dounya Kassimi. International Conference on Pattern Analysis and Intelligent Systems (PAIS), 2026. Cites: paper

PhysioNet as a global platform for biomedical research
Tom Pollard, Benjamin Moody, Li-wei H. Lehman et al. Nature Health, 2026. Cites: paper

From Sensing to Sense-Making: A Framework for On-Person Intelligence with Wearable Biosensors and Edge LLMs
Tad T. Brunyé, Mitchell V. Petrimoulx, Julie A. Cantelon. Sensors, 2026. Cites: paper

Binary Classification of Single-Lead Electrocardiogram Using Machine and Deep Learning Methods
Mariya R. Kiladze, Pavel Alekseyevich Lyakhov, Ruslan I. Abdulkadirov. International Russian Smart Industry Conference (SmartIndustryCon), 2026. Cites: paper

A Lightweight Hybrid Temporal CNN-Transformer Architecture for Real-Time Healthcare Anomaly Detection on Wearables
Akshit Naithani, Vrishin Jain. International Symposium on Digital Forensics and Security (ISDFS), 2026. Cites: paper

CoLDM: Componentwise Lead–Lag-Aware Dependence Modeling for Multivariate Time-Series Anomaly Detection in IoT
Yujia Fan, Wenhui Lin, Kexin Chen et al. IEEE Internet of Things Journal, 2026. Cites: paper

Correlation-Weighted KAN Attribution for Explainable AF Detection using Single-Lead ECG
Chandan Pandey, Anirban Dutta Choudhury, Tanuka Bhattacharjee et al. IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), 2026. Cites: paper

An augmented ECG data based classification for arrhythmia using optimal feature set
Mohammad Shahnawaz, Nikhil Kumawat, Tinku Singh et al. Health Information Science and Systems, 2026. Cites: paper

Cardiac health assessment across scenarios and devices using a multimodal foundation model pretrained on data from 1.7 million individuals
Xiao Gu, Wei Tang, Jinpei Han et al. Nature Machine Intelligence, 2026. Cites: paper

Lightweight Hybrid Neural Network for Enhanced ECG Signal Quality Assessment
Evgenia Slivko, Kay Bierzynski, Lorenzo Servadei et al. IEEE Applied Sensing Conference (APSCON), 2026. Cites: paper

Dynamic prediction of paroxysmal atrial fibrillation onset using longitudinal sample entropy in joint models
Nicolas Ngo, Aline Campos Reis de Souza, Roch Giorgi. BMC Medical Research Methodology, 2026. Cites: paper

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