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

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Showing 1–25 of 175 papers

TitleStatusHype
DBConformer: Dual-Branch Convolutional Transformer for EEG DecodingCode2
Residual and bidirectional LSTM for epileptic seizure detectionCode2
Dynamic GNNs for Precise Seizure Detection and Classification from EEG DataCode2
Scalable Machine Learning Architecture for Neonatal Seizure Detection on Ultra-Edge DevicesCode1
A foundation model with multi-variate parallel attention to generate neuronal activityCode1
Seizure Detection and Prediction by Parallel Memristive Convolutional Neural NetworksCode1
SzCORE: A Seizure Community Open-source Research Evaluation framework for the validation of EEG-based automated seizure detection algorithmsCode1
VSViG: Real-time Video-based Seizure Detection via Skeleton-based Spatiotemporal ViGCode1
SeizeIT2: Wearable Dataset Of Patients With Focal EpilepsyCode1
Modeling Multivariate Biosignals With Graph Neural Networks and Structured State Space ModelsCode1
Time series saliency maps: explaining models across multiple domainsCode1
ManyDG: Many-domain Generalization for Healthcare ApplicationsCode1
SeizureTransformer: Scaling U-Net with Transformer for Simultaneous Time-Step Level Seizure Detection from Long EEG RecordingsCode1
An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor AnalyticsCode1
Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure AnalysisCode1
BIOT: Cross-data Biosignal Learning in the WildCode1
Deep Latent Variable Modeling of Physiological SignalsCode1
Real-Time Seizure Detection using EEG: A Comprehensive Comparison of Recent Approaches under a Realistic SettingCode1
The Case for Cleaner Biosignals: High-fidelity Neural Compressor Enables Transfer from Cleaner iEEG to Noisier EEGCode1
Multi-Centroid Hyperdimensional Computing Approach for Epileptic Seizure DetectionCode0
Privacy-preserving Early Detection of Epileptic Seizures in VideosCode0
LightFF: Lightweight Inference for Forward-Forward AlgorithmCode0
Seizure Type Classification using EEG signals and Machine Learning: Setting a benchmarkCode0
MICAL: Mutual Information-Based CNN-Aided Learned FactorCode0
Privacy-Preserving Edge Federated Learning for Intelligent Mobile-Health SystemsCode0
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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