ECG Classification
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Benchmarks
Most implemented
Voice2Series: Reprogramming Acoustic Models for Time Series Classification
Zero-Shot ECG Classification with Multimodal Learning and Test-time Clinical Knowledge Enhancement
Anomaly Detection in Time Series with Triadic Motif Fields and Application in Atrial Fibrillation ECG Classification
Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL
Towards understanding ECG rhythm classification using convolutional neural networks and attention mappings
Deep Learning for ECG Classification
Papers
Test-Time Adaptation for ECG Classification via SQI-Gated Self-Training and Beat-Rhythm Consistency
Deep learning models for electrocardiogram (ECG) classification often suffer from significant performance degradation when deployed in unseen domains due to shifts in acquisition devices and patient populations. Test-tim…
Test-time AdaptationECG ClassificationHybrid Quantum-inspired Kolmogorov-Arnold Networks for Privacy-Aware Federated Biosignal Learning
Electrocardiogram (ECG) recordings are sensitive biomedical data, limiting the ability of hospitals and wearable devices to share raw signals for centralized model training. Federated learning addresses this practical pr…
Federated LearningECG ClassificationCardioState-JEPA: Delay-Aware Cross-Modal Learning of a Shared Cardiac Representation
Electrocardiography (ECG), photoplethysmography (PPG), and phonocardiography (PCG) provide complementary views of the same cardiac cycle, yet existing cardiac foundation models are trained for a single sensing modality, …
ECG ClassificationLSTrans: Efficient Knowledge Transfer for Lightweight and Automated ECG Classification
Deploying deep learning models for automated electrocardiogram classification on resource-constrained wearable devices remains challenging due to high computational costs. To address this, we propose LSTrans, a lightweig…
Knowledge DistillationECG ClassificationDual Attention Heads for Personalized Federated Learning in ECG Classification
Federated learning (FL) enables collaborative model training across institutions without sharing sensitive patient data. However, the inherent heterogeneity of electrocardiogram (ECG) data across healthcare providers pre…
Personalized Federated LearningECG ClassificationUsing Explainability as a Training-Time Reliability Signal for Efficient ECG Classification
Training deep neural networks for clinical time-series analysis is computationally demanding, yet many healthcare settings lack the resources required for repeated model development and deployment. This challenge is part…
ECG Classification