SOTAVerified

ECG Classification

Papers

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Showing 26–50 of 116 papers

TitleStatusHype
Transfer Learning in ECG Diagnosis: Is It Effective?Code0
Guiding Masked Representation Learning to Capture Spatio-Temporal Relationship of ElectrocardiogramCode2
Reading Between the Leads: Local Lead-Attention Based Classification of Electrocardiogram SignalsCode0
Automatic ECG classification using discrete wavelet transform and one-dimensional convolutional neural networkCode1
MPCNN: A Novel Matrix Profile Approach for CNN-based Sleep Apnea ClassificationCode1
Graph Neural Networks for Topological Feature Extraction in ECG Classification—0
MELEP: A Novel Predictive Measure of Transferability in Multi-Label ECG DiagnosisCode0
Cloud-Connected Wireless Holter Monitor Machine with Neural Networks Based ECG Analysis for Remote Health Monitoring—0
Masked Transformer for Electrocardiogram Classification—0
Optimizing Neural Network Scale for ECG Classification—0
ECG classification using Deep CNN and Gramian Angular Field—0
MSW-Transformer: Multi-Scale Shifted Windows Transformer Networks for 12-Lead ECG Classification—0
Multi-Label ECG Classification using Temporal Convolutional Neural Network—0
Transforming ECG Diagnosis:An In-depth Review of Transformer-based DeepLearning Models in Cardiovascular Disease Detection—0
Deep Neural Networks Generalization and Fine-Tuning for 12-lead ECG Classification—0
PulseNet: Deep Learning ECG-signal classification using random augmentation policy and continous wavelet transform for canines—0
Arrhythmia Classifier Based on Ultra-Lightweight Binary Neural NetworkCode1
Side Channel-Assisted Inference Leakage from Machine Learning-based ECG Classification—0
ECG Classification System for Arrhythmia Detection Using Convolutional Neural NetworksCode0
MVKT-ECG: Efficient Single-lead ECG Classification on Multi-Label Arrhythmia by Multi-View Knowledge Transferring—0
Proof of Swarm Based Ensemble Learning for Federated Learning Applications—0
A Dual-scale Lead-seperated Transformer With Lead-orthogonal Attention And Meta-information For Ecg Classification—0
Advancing the State-of-the-Art for ECG Analysis through Structured State Space ModelsCode1
Analysis of a Deep Learning Model for 12-Lead ECG Classification Reveals Learned Features Similar to Diagnostic Criteria—0
SEVGGNet-LSTM: a fused deep learning model for ECG classification—0
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All datasetsPhysioNet Challenge 2021Electrocardiography (ECG) on Telehealth Network of Minas Gerais (TNMG)PhysioNet Challenge 2020PTB-XLUCR Time Series Classification Archive

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Local Lead AttentionPhysioNet Challenge score 20210.52—Unverified
2Classifier Chain (3-lead)PhysioNet Challenge score 2021-0.6—Unverified
3Classifier Chain (2-lead)PhysioNet Challenge score 2021-0.63—Unverified
4Classifier Chain (4-lead)PhysioNet Challenge score 2021-0.63—Unverified
5Classifier Chain (6-lead)PhysioNet Challenge score 2021-0.63—Unverified
#ModelMetricClaimedVerifiedStatus
1DNNF1 (1dAVb)0.89—Unverified
24th year cardiology residentF1 (1dAVb)0.78—Unverified
35th year medical studentF1 (1dAVb)0.73—Unverified
43rd year emergency residentF1 (1dAVb)0.72—Unverified
#ModelMetricClaimedVerifiedStatus
11D CNN EncoderPhysioNet Challenge score (test data)0.21—Unverified
#ModelMetricClaimedVerifiedStatus
1xresnet1d101AUROC0.93—Unverified
#ModelMetricClaimedVerifiedStatus
1V2SaAccuracy (Test)93.96—Unverified