Seizure prediction

7 papers with code • 1 benchmarks • 1 datasets

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Most implemented papers

Learning Optimized Risk Scores

ustunb/risk-slim 1 Oct 2016

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

ostojanovic/seizure_prediction medrxiv, PLOS ONE (under review) 2019

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

SuperBruceJia/EEG-DL 25 Jun 2020

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

MauroSilvaPinto/A-personalized-and-evolutionary-algorithm-for-interpretable-EEG-epilepsy-seizure-prediction Scientific Reports 2021

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

chmendoza/cspwave 25 Mar 2021

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

MauroSilvaPinto/Interpretable-EEG-seizure-prediction-using-a-multiobjective-evolutionary-algorithm Scientific Reports 2022

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.