Detection of epileptic seizure from EEG signal data by employing machine learning algorithms with hyperparameter optimization
AA Rahman, F Faisal, MM Nishat… - … Conference on Bio …, 2021 - ieeexplore.ieee.org
Epileptic seizure refers to a brief occurrence of signs in the brain caused by abnormally high
or synchronized neuronal activity. With the utilization of EEG signal, the epileptic seizure can …
or synchronized neuronal activity. With the utilization of EEG signal, the epileptic seizure can …
New approach for automated epileptic disease diagnosis using an integrated self-organization map and radial basis function neural network algorithm
AH Osman, AA Alzahrani - IEEE Access, 2018 - ieeexplore.ieee.org
Currently, epilepsy disease (ED) is considered to be one of the gradual diseases in brain
function over a period of several months or years. Seizure status is the primary common …
function over a period of several months or years. Seizure status is the primary common …
Classification of time realizations using machine learning recognition of recurrence plots
L Kirichenko, P Zinchenko, T Radivilova - … Conference “Intellectual Systems …, 2020 - Springer
In the article, the machine learning classification of time realizations using the recurrence
plot visualization is considered. Every time realization is converted into a matrix of …
plot visualization is considered. Every time realization is converted into a matrix of …
BERT learns from electroencephalograms about Parkinson's disease: transformer-based models for aid diagnosis
A Nogales, ÁJ García-Tejedor, AM Maitín… - IEEE …, 2022 - ieeexplore.ieee.org
Medicine is a complex field with highly trained specialists with extensive knowledge that
continuously needs updating. Among them all, those who study the brain can perform …
continuously needs updating. Among them all, those who study the brain can perform …
Epileptic seizures classification in EEG using PCA based genetic algorithm through machine learning
MKM Rabby, AKMK Islam, S Belkasim… - Proceedings of the 2021 …, 2021 - dl.acm.org
In this research, a Principal Component Analysis (PCA) with Genetic Algorithm based
Machine Learning (ML) approach is developed for the binary classification of epileptic …
Machine Learning (ML) approach is developed for the binary classification of epileptic …
A comparative study of machine learning algorithms for epileptic seizure classification on EEG signals
Electroencephalography (EEG) 1s a tool for monitoring brain activity which is important for
identifying epilepsy seizure. Automatic epileptic seizure identification in EEG is a …
identifying epilepsy seizure. Automatic epileptic seizure identification in EEG is a …
A machine learning model to predict seizure susceptibility from resting-state fMRI connectivity
Traumatic brain injury (TBI) is a leading cause of disability globally. Many patients develop
post-traumatic epilepsy, or recurrent seizures following TBI. In recent years, significant efforts …
post-traumatic epilepsy, or recurrent seizures following TBI. In recent years, significant efforts …
Wavelet transform-based feature extraction approach for epileptic seizure classification
MKM Rabby, AKMK Islam, S Belkasim… - Proceedings of the 2021 …, 2021 - dl.acm.org
In this research, a wavelet transform-based feature extraction approach is proposed for the
detection of epileptic seizures from the EEG raw dataset. The proposed approach uses the …
detection of epileptic seizures from the EEG raw dataset. The proposed approach uses the …
Quantitative EEG features selection in the classification of attention and response control in the children and adolescents with attention deficit hyperactivity disorder
Aim: Quantitative EEG gives valuable information in the clinical evaluation of psychological
disorders. The purpose of the present study is to identify the most prominent features of …
disorders. The purpose of the present study is to identify the most prominent features of …
[HTML][HTML] Performance analysis of fuzzy multilayer support vector machine for epileptic seizure disorder classification using auto regression features
T Rajendran, KP Sridhar… - The Open …, 2019 - openbiomedicalengineeringjournal …
Background: Around 1% of the total population in the world suffers from epilepsy, a central
nervous system disorder. Epilepsy is the neurological disorder of the human brain which can …
nervous system disorder. Epilepsy is the neurological disorder of the human brain which can …