Seizure prediction
8 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Seizure prediction
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TUH EEG Seizure Corpus
Most implemented papers
Learning Optimized Risk Scores
Risk scores are simple classification models that let users make quick risk predictions by adding and subtracting a few small numbers.
Predicting epileptic seizures using nonnegative matrix factorization
The resulting method yields a computationally and conceptually simple, interpretable model of EEG signals of preictal and interictal states, which shows a good performance for the task of seizure prediction.
Attention-based Graph ResNet for Motor Intent Detection from Raw EEG signals
In previous studies, decoding electroencephalography (EEG) signals has not considered the topological relationship of EEG electrodes.
A personalized and evolutionary algorithm for interpretable EEG epilepsy seizure prediction
Seizure prediction may improve the quality of life of patients suffering from drug-resistant epilepsy, which accounts for about 30% of the total epileptic patients.
Searching for waveforms on spatially-filtered epileptic ECoG
Seizures are one of the defining symptoms in patients with epilepsy, and due to their unannounced occurrence, they can pose a severe risk for the individual that suffers it.
Interpretable EEG seizure prediction using a multiobjective evolutionary algorithm
We also compared our results with a control method based on the standard machine learning pipeline (pre-processing, feature extraction, classifier training, and post-processing), where the control marginally outperformed our approach by validating 35% of the patients.
Seizure Detection and Prediction by Parallel Memristive Convolutional Neural Networks
coreylammie/memristive-seizure-detection-and-prediction-by-parallel-convolutional-neural-networks
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During the past two decades, epileptic seizure detection and prediction algorithms have evolved rapidly.
A library of quantitative markers of seizure severity
In individual patients, 71% had a moderate to large difference (ranksum r > 0. 3) between focal and subclinical seizures in three or more markers.
