Thesis project: "On the clinical acceptance of EEG seizure prediction methodologies". Explainability of seizure prediction models.
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Updated
Sep 28, 2022 - Python
Thesis project: "On the clinical acceptance of EEG seizure prediction methodologies". Explainability of seizure prediction models.
American Epilepsy Society Seizure Prediction Challenge.
Computational Artificial Intelligence Projects (Seizure Detection) - Fall-2022
Epileptic EEG detection using the linear prediction error energy
kaggle competition: seizure prediction
Seizure prediction contains innovative methods using adaptive filtering for detecting epileptic seizures based on energy signals
Hidden Markov Models for Epilepsy Data
This project focuses on predicting epileptic seizures using EEG signals and ensemble learning techniques. It aims to provide accurate and timely predictions to help individuals with epilepsy manage their condition more effectively.
The codebase for a research project that uses common spatial patterns (CSP) filters to search for waveforms in epileptic Electrocorticographic (ECoG) signals that are discriminative of the preictal and interictal state.
on-line seizure prediction by evolve neuro-fuzzy model based on SOP and SPH
The code for the paper "The goal of explaining black boxes in EEG seizure prediction is not to explain models’ decisions", published in Epilepsia Open (https://doi.org/10.1002/epi4.12748). It concerns explainability methods on Machine Learning for EEG seizure prediction.
based on kaggle's Melbourne University AES/MathWorks/NIH competition
In this research project we used a shift-invariant k-means algorithm to learn a preictal and interictal codebook of prototypical waveforms that can be used to summarize the occurrence of recurrent waveforms and to classify between preictal and interictal segments. We use the common spatial patterns (CSP) method to spatially filter the multichann…
Epilepsey and Insomnia Detection Using EEG signals
Epilepsy Prediction with CNN-BiLSTM | BSc dissertation project
Code and data of the paper "A personalized and evolutionary algorithm for interpretable EEG epilepsy seizure prediction", published by Scientific Reports in 2021.
Code and data of the paper "Interpretable EEG seizure prediction using a multiobjective evolutionary algorithm", published by Scientific Reports in 2022.
Real-time Forecasting Epileptic Seizure using EEG
This repository contains the trained deep learning models for the detection and prediction of Epileptic seizures.
2nd place algorithm for Melbourne-University AES-MathWorks-NIH Seizure Prediction Challenge
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