SOTAVerified

Seizure Detection

Seizure Detection is a binary supervised classification problem with the aim of classifying between seizure and non-seizure states of a patient.

Source: ResOT: Resource-Efficient Oblique Trees for Neural Signal Classification

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–175 of 175 papers

TitleStatusHype
Reporting existing datasets for automatic epilepsy diagnosis and seizure detection—0
Seizure Type Classification using EEG signals and Machine Learning: Setting a benchmarkCode0
LightFF: Lightweight Inference for Forward-Forward AlgorithmCode0
Synthetic Epileptic Brain Activities Using Generative Adversarial NetworksCode0
MICAL: Mutual Information-Based CNN-Aided Learned FactorCode0
Semi-Supervised Learning for Sparsely-Labeled Sequential Data: Application to Healthcare Video ProcessingCode0
Systematic Assessment of Hyperdimensional Computing for Epileptic Seizure DetectionCode0
Multi-Centroid Hyperdimensional Computing Approach for Epileptic Seizure DetectionCode0
Adversarial Representation Learning for Robust Patient-Independent Epileptic Seizure DetectionCode0
Learning Robust Representations of Tonic-Clonic Seizures With Cyclic TransformerCode0
Change Detection in Graph Streams by Learning Graph Embeddings on Constant-Curvature ManifoldsCode0
Learning Robust Features using Deep Learning for Automatic Seizure DetectionCode0
Efficient Epileptic Seizure Detection Using CNN-Aided Factor GraphsCode0
ScatterFormer: Locally-Invariant Scattering Transformer for Patient-Independent Multispectral Detection of Epileptiform DischargesCode0
Exploration of Hyperdimensional Computing Strategies for Enhanced Learning on Epileptic Seizure DetectionCode0
TRUST-LAPSE: An Explainable and Actionable Mistrust Scoring Framework for Model MonitoringCode0
An Open-source Toolbox for Analysing and Processing PhysioNet Databases in MATLAB and OctaveCode0
Avoiding Post-Processing with Event-Based Detection in Biomedical SignalsCode0
Towards Interpretable Seizure Detection Using WearablesCode0
The use of Multi-domain Electroencephalogram Representations in the building of Models based on Convolutional and Recurrent Neural Networks for Epilepsy DetectionCode0
Privacy-preserving Early Detection of Epileptic Seizures in VideosCode0
Privacy-Preserving Edge Federated Learning for Intelligent Mobile-Health SystemsCode0
SeizureNet: Multi-Spectral Deep Feature Learning for Seizure Type ClassificationCode0
Ensemble learning using individual neonatal data for seizure detectionCode0
Using Explainable AI for EEG-based Reduced Montage Neonatal Seizure DetectionCode0
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All datasetsTUH EEG Seizure CorpusCHB-MIT

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ResNet+ LSTMAUROC0.92—Unverified
2CNN2D+LSTMAUROC0.92—Unverified
#ModelMetricClaimedVerifiedStatus
1TF-Tensor-CNNAccuracy89.63—Unverified