Machine learning algorithms for epilepsy detection based on published EEG databases: A systematic review
Epilepsy is the only neurological condition for which electroencephalography (EEG) is the
primary diagnostic and important prognostic clinical tool. However, the manual inspection of …
primary diagnostic and important prognostic clinical tool. However, the manual inspection of …
Quantitative analysis of EEG reactivity for neurological prognostication after cardiac arrest
Objective To test whether 1) quantitative analysis of EEG reactivity (EEG-R) using machine
learning (ML) is superior to visual analysis, and 2) combining quantitative analyses of EEG …
learning (ML) is superior to visual analysis, and 2) combining quantitative analyses of EEG …
Detection and Classification of ADHD from EEG Signals Using Tunable Q‐Factor Wavelet Transform
The automatic identification of Attention Deficit Hyperactivity Disorder (ADHD) is essential for
developing ADHD diagnosis tools that assist healthcare professionals. Recently, there has …
developing ADHD diagnosis tools that assist healthcare professionals. Recently, there has …
Automated multi-class seizure-type classification system using EEG signals and machine learning algorithms
Epilepsy is a chronic brain disorder characterized by recurrent unprovoked seizures. The
treatment for epilepsy is influenced by the types of seizures. Therefore, developing a …
treatment for epilepsy is influenced by the types of seizures. Therefore, developing a …
Lung sound classification using multiresolution Higuchi fractal dimension measurement.
Lung sound is one indicator of abnormalities in the lungs and respiratory tract. Research for
automatic lung sound classification has become one of the interests for researchers …
automatic lung sound classification has become one of the interests for researchers …
Combination of Coarse-Grained Procedure and Fractal Dimension for Epileptic EEG Classification
Epilepsy, cured by some offered treatments such as medication, surgery, and dietary plan, is
a neurological brain disorder due to disturbed nerve cell activity characterized by repeated …
a neurological brain disorder due to disturbed nerve cell activity characterized by repeated …
[PDF][PDF] Research Article Detection and Classification of ADHD from EEG Signals Using Tunable Q-Factor Wavelet Transform
The automatic identification of Attention Deficit Hyperactivity Disorder (ADHD) is essential for
developing ADHD diagnosis tools that assist healthcare professionals. Recently, there has …
developing ADHD diagnosis tools that assist healthcare professionals. Recently, there has …