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 51–100 of 175 papers

TitleStatusHype
Deep Learning Approaches for Seizure Video Analysis: A Review—0
Seizure detection from Electroencephalogram signals via Wavelets and Graph Theory metrics—0
VSViG: Real-time Video-based Seizure Detection via Skeleton-based Spatiotemporal ViGCode1
Enhancing Epileptic Seizure Detection with EEG Feature Embeddings—0
Privacy-preserving Early Detection of Epileptic Seizures in VideosCode0
EpiDeNet: An Energy-Efficient Approach to Seizure Detection for Embedded Systems—0
Protecting the Future: Neonatal Seizure Detection with Spatial-Temporal Modeling—0
Ongoing EEG artifact correction using blind source separation—0
Reporting existing datasets for automatic epilepsy diagnosis and seizure detection—0
MBrain: A Multi-channel Self-Supervised Learning Framework for Brain Signals—0
Machine Learning Based IoT Adaptive Architecture for Epilepsy Seizure Detection: Anatomy and Analysis—0
BIOT: Cross-data Biosignal Learning in the WildCode1
Lightweight Convolution Transformer for Cross-patient Seizure Detection in Multi-channel EEG Signals—0
Towards Interpretable Seizure Detection Using WearablesCode0
ScatterFormer: Locally-Invariant Scattering Transformer for Patient-Independent Multispectral Detection of Epileptiform DischargesCode0
Supervised and Unsupervised Deep Learning Approaches for EEG Seizure Prediction—0
Knowledge-Distilled Graph Neural Networks for Personalized Epileptic Seizure Detection—0
Importance of methodological choices in data manipulation for validating epileptic seizure detection models—0
Novel Epileptic Seizure Detection Techniques and their Empirical Analysis—0
ManyDG: Many-domain Generalization for Healthcare ApplicationsCode1
Shorter Latency of Real-time Epileptic Seizure Detection via Probabilistic Prediction—0
EEG Opto-processor: epileptic seizure detection using diffractive photonic computing units—0
Modeling Multivariate Biosignals With Graph Neural Networks and Structured State Space ModelsCode1
Topological biomarkers for real-time detection of epileptic seizures—0
A Meta-GNN approach to personalized seizure detection and classification—0
A review on Epileptic Seizure Detection using Machine Learning—0
Avoiding Post-Processing with Event-Based Detection in Biomedical SignalsCode0
Classification of eye-state using EEG recordings: speed-up gains using signal epochs and mutual information measure—0
Six-center Assessment of CNN-Transformer with Belief Matching Loss for Patient-independent Seizure Detection in EEG—0
TRUST-LAPSE: An Explainable and Actionable Mistrust Scoring Framework for Model MonitoringCode0
Many-to-One Knowledge Distillation of Real-Time Epileptic Seizure Detection for Low-Power Wearable Internet of Things Systems—0
Improving self-supervised pretraining models for epileptic seizure detection from EEG data—0
Seizure Detection and Prediction by Parallel Memristive Convolutional Neural NetworksCode1
MICAL: Mutual Information-Based CNN-Aided Learned FactorCode0
Hyperdimensional computing encoding for feature selection on the use case of epileptic seizure detection—0
Energy-Efficient Tree-Based EEG Artifact Detection—0
Ensemble learning using individual neonatal data for seizure detectionCode0
CNN-Aided Factor Graphs with Estimated Mutual Information Features for Seizure Detection—0
Validating an SVM-based neonatal seizure detection algorithm for generalizability, non-inferiority and clinical efficacy—0
Low Latency Real-Time Seizure Detection Using Transfer Deep Learning—0
Significant Low-dimensional Spectral-temporal Features for Seizure Detection—0
Exploration of Hyperdimensional Computing Strategies for Enhanced Learning on Epileptic Seizure DetectionCode0
Real-Time Seizure Detection using EEG: A Comprehensive Comparison of Recent Approaches under a Realistic SettingCode1
Scalable Machine Learning Architecture for Neonatal Seizure Detection on Ultra-Edge DevicesCode1
Multi-Centroid Hyperdimensional Computing Approach for Epileptic Seizure DetectionCode0
A Time-Series Scale Mixture Model of EEG with a Hidden Markov Structure for Epileptic Seizure Detection—0
Automated Human Mind Reading Using EEG Signals for Seizure Detection—0
Epileptic Seizure Classification Using Combined Labels and a Genetic Algorithm—0
SOUL: An Energy-Efficient Unsupervised Online Learning Seizure Detection Classifier—0
TIME-LAPSE: Learning to say “I don't know” through spatio-temporal uncertainty scoring—0
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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