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

Desarrollo de nuevos marcadores y clasificadores de bajo coste computacional para identificar afecciones cardiacas en registros ECG
Santiago Jiménez Serrano. 2023. Cites: paper

RR Interval-based Atrial Fibrillation Detection using Traditional and Ensemble Machine Learning Algorithms
Shrikanth Rao S.K, Roshan Joy Martis. Journal of Medical Signals & Sensors, 2023. Cites: paper

A Data Quality Measurement Framework Using Distribution-Based Modeling and Simulation in Real-Time Telemedicine Systems
Zoltán Richárd Jánki, Vilmos Bilicki. Applied Sciences, 2023. Cites: paper

HV geometry for signal comparison
Ruiyu Han, Dejan Slepčev, Yunan Yang. Quarterly of Applied Mathematics, 2023. Cites: paper

On the Atrial Fibrillation Detection Performance of ECG-DualNet
Christoph Reich, Maurice Rohr, Tim Kircher et al. medRxiv, 2023. Cites: paper

Deep Spectral Features to Detect Atrial Fibrillation using Single-Lead ECG Signals
Siddhi K. Bajracharya, Rodrigue Rizk, KC Santosh. IEEE Conference on Artificial Intelligence (CAI), 2023. Cites: paper

A Systematic Survey of Data Augmentation of ECG Signals for AI Applications
Md Moklesur Rahman, Massimo Walter Rivolta, Fabio Badilini et al. Sensors, 2023. Cites: paper

FGSQA-Net: A Weakly Supervised Approach to Fine-Grained Electrocardiogram Signal Quality Assessment
Hui Liu, Tianlei Gao, Zhaoyang Liu et al. IEEE Journal of Biomedical and Health Informatics, 2023. Cites: paper

Detection of Paroxysmal Atrial Fibrillation from Dynamic ECG Recordings Based on a Deep Learning Model
Yating Hu, Tengfei Feng, Miao Wang et al. Journal of Personalized Medicine, 2023. Cites: paper

Atrial Fibrillation (AF) Detection Using Deep Learning with GAN-based Data Augmentation
Amirhossein Akhoondkazemi, Arash Vashagh, Sayed Jalal Zahabi et al. 2023. Cites: paper

Design an Intelligent Real Time ECG Monitoring System Using Convolution Neural Network
Hiba Mahdi Falhi, Hussain Kareem Khleaf. Revue d intelligence artificielle, 2023. Cites: paper

Leveraging physiology and artificial intelligence to deliver advancements in health care
Angela Zhang, Zhenqin Wu, Eric Wu et al. Physiological Reviews, 2023. Cites: paper

Diagnosis of atrial fibrillation using self-complementary attentional convolutional neural network
Yongjian Li, Liting Zhang, Lin Zhu et al. Computer Methods and Programs in Biomedicine, 2023. Cites: paper

Self-Supervised Contrastive Learning for Medical Time Series: A Systematic Review
Ziyu Liu, Azadeh Alavi, Minyi Li et al. Sensors, 2023. Cites: paper

Current and Future Use of Artificial Intelligence in Electrocardiography
Manuel Martínez‐Sellés, Manuel Marina Breysse. Journal of Cardiovascular Development and Disease, 2023. Cites: paper

Applications of Self-Supervised Learning to Biomedical Signals: where are we now
Federico Del Pup, Manfredo Atzori. 2023. Cites: paper

Novel HRV Metrics using Analytic Signal Representation of Interbeat Intervals for New Insights on Cardiac Dynamics
Sawon Pratiher, Apoorva Srivastava, Mrinal Acharya et al. 2023. Cites: paper

A Study of R-R Interval Transition Matrix Features for Machine Learning Algorithms in AFib Detection
Sahil Patel, Maximilian Wang, Justin Guo et al. Sensors, 2023. Cites: paper

Lossless Sparse Temporal Coding for SNN-based Classification of Time-Continuous Signals
Johnson Loh, Tobias Gemmeke. Design, Automation, and Test in Europe, 2023. Cites: paper

A Temporal Transformer-Based Fusion Framework for Morphological Arrhythmia Classification
Nafisa Anjum, Khaleda Akhter Sathi, Md. Azad Hossain et al. Computers, 2023. Cites: paper

An ECG Stitching Scheme for Driver Arrhythmia Classification Based on Deep Learning
Do‐Hoon Kim, Gwangjin Lee, Seong Han Kim. Sensors, 2023. Cites: paper

Atrial fibrillation detection using Poincare geometry and heart beat intervals
Shrikanth Rao S.K, Maheshkumar H. Kolekar, Roshan Joy Martis. Expert Systems, 2023. Cites: paper

Detection of Fibrillatory Episodes in Atrial Fibrillation Rhythms via Topology-informed Machine Learning
Paul Samuel Ignacio. 2023. Cites: paper

Electrocardiogram Heartbeat Classification for Arrhythmias and Myocardial Infarction
Bach-Tung Pham, Phuong Thi Le, Tzu-Chiang Tai et al. Sensors, 2023. Cites: paper

Morphological Autoencoders for Beat-by-Beat Atrial Fibrillation Detection Using Single-Lead ECG
Rafael Silva, Ana L. N. Fred, Hugo Silva. Sensors, 2023. Cites: paper

DeepMiceTL: a deep transfer learning based prediction of mice cardiac conduction diseases using early electrocardiograms
Ying Liao, Yisha Xiang, Mingjie Zheng et al. Briefings in Bioinformatics, 2023. Cites: paper

The Role of Morphology and Heart Rate Variability Features in Detecting Arrhythmias from Short ECGs
Alice Hu, Shadi Ghiasi. Journal of Student Research, 2023. Cites: paper

Pre-training in Medical Data: A Survey
Yixuan Qiu, Feng Lin, Weitong Chen et al. Machine Intelligence Research, 2023. Cites: paper

Multi-Modal Stacking Ensemble for the Diagnosis of Cardiovascular Diseases
Taeyoung Yoon, Daesung Kang. Journal of Personalized Medicine, 2023. Cites: paper

A Deep Learning Architecture Using 3D Vectorcardiogram to Detect R-Peaks in ECG with Enhanced Precision
Maroua Mehri, Guillaume Calmon, Freddy Odille et al. Sensors, 2023. Cites: paper

A Review on Heartbeat Classification for Arrhythmia Detection Using ECG signal Processing
Praveen Kumar Tyagi, Neha Rathore, Dheeraj Agrawal. IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS), 2023. Cites: paper

Atrial fibrillation classification based on the 2D representation of minimal subset ECG and a non-deep neural network
Hua Zhang, Chengyu Liu, Fangfang Tang et al. Frontiers in Physiology, 2023. Cites: paper

Algorithms for automated diagnosis of cardiovascular diseases based on ECG data: A comprehensive systematic review
Hanna Vitaliyivna Denysyuk, Rui João Pinto, Pedro Miguel Silva et al. Heliyon, 2023. Cites: paper

An overview on state-of-the-art electrocardiogram signal processing methods: Traditional to AI-based approaches
Venkata Anuhya Ardeti, Venkata Ratnam Kolluru, George Tom Varghese et al. Expert Systems with Applications, 2023. Cites: paper

A training pipeline of an arrhythmia classifier for atrial fibrillation detection using Photoplethysmography signal
Sota Kudo, Zheng Chen, Xue Mei Zhou et al. Frontiers in Physiology, 2023. Cites: paper

A deep learning model for the classification of atrial fibrillation in critically ill patients
Brian Chen, David M. Maslove, Jeffrey D. Curran et al. Intensive Care Medicine Experimental, 2023. Cites: paper

Adaptive short-time Fourier transform based on reinforcement learning
Weikun Zhao, Chaofeng Wang, Ya Ping Jiang et al. International Conference on Consumer Electronics and Computer Engineering (ICCECE), 2023. Cites: paper

A Light Weight Cardiac Monitoring System for On-device ECG Analysis
Rohan Banerjee, Avik Ghose. Lecture notes in computer science, 2023. Cites: paper

A Light-Weight Deep Residual Network for Classification of Abnormal Heart Rhythms on Tiny Devices
Rohan Banerjee, Avik Ghose. Communications in computer and information science, 2023. Cites: paper

A Personal Health Agent for Decision Support in Arrhythmia Diagnosis
Tezira Wanyana, Mbithe Nzomo, Catherine Susan Price et al. Communications in computer and information science, 2023. Cites: paper

Applications of Self-Supervised Learning to Biomedical Signals: A Survey
Federico Del Pup, Manfredo Atzori. IEEE Access, 2023. Cites: paper

A Transition-Boosted Hashing for ECG Biometrics
Yixian Fang, Canwei Wang, Feng Yuan et al. Lecture notes in electrical engineering, 2023. Cites: paper

Atrial Fibrillation Detection with Low Signal‐to‐Noise Ratio Data Using Artificial Features and Abstract Features
Zhe Bao, Dong Li, Jiang Shou-fen et al. Journal of Healthcare Engineering, 2023. Cites: paper

Atrial Fibrillation Detection With Spectral Manifolds in Low-Dimensional Latent Spaces
C. P. Bernal, Enrique V. Carrera, Francisco-Manuel Melgarejo-Meseguer et al. IEEE Access, 2023. Cites: paper

Bskdecg: A Novel Balanced Self-Supervised Knowledge Distillation Framework for Electrocardiogram Arrhythmia Diagnosis of Wearable Devices
Yong Wang, An Chunyan, Wenming Yang et al. SSRN Electronic Journal, 2023. Cites: paper

Cognitive Assistant for Enhanced eHealth Monitoring
Jaime Andres Rincon, Cédric Marco-Detchart, Vicente Julián. Lecture notes in computer science, 2023. Cites: paper

Comparison of Supervised Learning Algorithms for Quality Assessment of Wearable Electrocardiograms With Paroxysmal Atrial Fibrillation
Álvaro Huerta Herráiz, Arturo Martínez‐Rodrigo, Davide Rua Carneiro et al. IEEE Access, 2023. Cites: paper

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