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
A foundation model with multi-variate parallel attention to generate neuronal activityCode1
EEG-Based Inter-Patient Epileptic Seizure Detection Combining Domain Adversarial Training with CNN-BiLSTM Network—0
SzCORE as a benchmark: report from the seizure detection challenge at the 2025 AI in Epilepsy and Neurological Disorders Conference—0
Time series saliency maps: explaining models across multiple domainsCode1
Machine-Learning-Powered Neural Interfaces for Smart Prosthetics and Diagnostics—0
The use of Multi-domain Electroencephalogram Representations in the building of Models based on Convolutional and Recurrent Neural Networks for Epilepsy DetectionCode0
Augmentation of EEG and ECG Time Series for Deep Learning Applications: Integrating Changepoint Detection into the iAAFT Surrogates—0
SeizureTransformer: Scaling U-Net with Transformer for Simultaneous Time-Step Level Seizure Detection from Long EEG RecordingsCode1
Improving Neonatal Care: An Active Dry-Contact Electrode-based Continuous EEG Monitoring System with Seizure Detection—0
Automated Video-EEG Analysis in Epilepsy Studies: Advances and Challenges—0
BioSerenity-E1: a self-supervised EEG model for medical applications—0
MT-NAM: An Efficient and Adaptive Model for Epileptic Seizure Detection—0
The Case for Cleaner Biosignals: High-fidelity Neural Compressor Enables Transfer from Cleaner iEEG to Noisier EEGCode1
SeizeIT2: Wearable Dataset Of Patients With Focal EpilepsyCode1
CEReBrO: Compact Encoder for Representations of Brain Oscillations Using Efficient Alternating Attention—0
Automated Detection of Epileptic Spikes and Seizures Incorporating a Novel Spatial Clustering Prior—0
A Systematic Review of Machine Learning Methods for Multimodal EEG Data in Clinical Application—0
Canine EEG Helps Human: Cross-Species and Cross-Modality Epileptic Seizure Detection via Multi-Space Alignment—0
Real-time Sub-milliwatt Epilepsy Detection Implemented on a Spiking Neural Network Edge Inference Processor—0
BUNDL: Bayesian Uncertainty-aware Deep Learning with Noisy training Labels for Seizure Detection in EEG—0
From Epilepsy Seizures Classification to Detection: A Deep Learning-based Approach for Raw EEG Signals—0
Designing Pre-training Datasets from Unlabeled Data for EEG Classification with Transformers—0
MetaWearS: A Shortcut in Wearable Systems Lifecycle with Only a Few Shots—0
Efficient Patient Fine-Tuned Seizure Detection with a Tensor Kernel Machine—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