Atrial Fibrillation Detection
2개 벤치마크 · 논문 50편 · 이 태스크의 논문 보기 →
Benchmarks
MIT-BIH AF
PhysioNet Challenge 2017
Most implemented
Anomaly Detection in Time Series with Triadic Motif Fields and Application in Atrial Fibrillation ECG Classification
BayesBeat: Reliable Atrial Fibrillation Detection from Noisy Photoplethysmography Data
Efficient Multi-View Fusion and Flexible Adaptation to View Missing in Cardiovascular System Signals
SQUWA: Signal Quality Aware DNN Architecture for Enhanced Accuracy in Atrial Fibrillation Detection from Noisy PPG Signals
Papers
Atrial Fibrillation Detection with Arbitrary Leads via a Codebook-Based Reconstruction-Classification Framework
\textbf{Background and Objective}: Reliable atrial fibrillation (AF) detection from electrocardiogram (ECG) signals remains challenging in real-world clinical settings due to variable lead configurations, cross-dataset d…
Atrial Fibrillation DetectionFOUND-AF: Benchmarking ECG Foundation Models for Atrial Fibrillation Detection
Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and is associated with increased risks of stroke, heart failure, and mortality. Recent ECG foundation models offer transferable representations for…
Atrial Fibrillation DetectionComputational EfficiencySampling Matters: The Effect of ECG Frequency on Deep Learning-Based Atrial Fibrillation Detection
Deep learning models for atrial fibrillation (AF) detection are increasingly trained on heterogeneous electrocardiogram (ECG) datasets with varying sampling frequencies, yet the specific consequences of these discrepanci…
Atrial Fibrillation DetectionArrhythmia DetectionECG-RAMBA: Zero-Shot ECG Generalization by Morphology-Rhythm Disentanglement and Long-Range Modeling
Deep learning has achieved strong performance for electrocardiogram (ECG) classification within individual datasets, yet dependable generalization across heterogeneous acquisition settings remains a major obstacle to cli…
Atrial Fibrillation DetectionTest-time AdaptationLong-range modelingA Dataset and Benchmarks for Atrial Fibrillation Detection from Electrocardiograms of Intensive Care Unit Patients
Objective: Atrial fibrillation (AF) is the most common cardiac arrhythmia experienced by intensive care unit (ICU) patients and can cause adverse health effects. In this study, we publish a labelled ICU dataset and bench…
Atrial Fibrillation DetectionTransfer LearningPPG-Distill: Efficient Photoplethysmography Signals Analysis via Foundation Model Distillation
Photoplethysmography (PPG) is widely used in wearable health monitoring, yet large PPG foundation models remain difficult to deploy on resource-limited devices. We present PPG-Distill, a knowledge distillation framework …
Atrial Fibrillation DetectionKnowledge DistillationHeart rate estimation