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Neural Network Based Response Prediction of rTMS in Major Depressive Disorder Using QEEG Cordance
(2015-01-12)
ObjectiveaaThe combination of repetitive transcranial magnetic stimulation (rTMS), a non-pharmacological form of therapy for treating major depressive disorder (MDD), and electroencephalogram (EEG) is a valuable tool for ...
Ant Colony Optimization Based Feature Selection Method for QEEG Data Classification
(Psychiatry Investigation, 2014)
Objective:Many applications such as biomedical signals require selecting a subset of the input features in order to represent the whole set of features. A feature selection algorithm has recently been proposed as a new ...
Feature Selection and Classification of Electroencephalographic Signals: An Artificial Neural Network and Genetic Algorithm Based Approach
(Clinical EEG and Neuroscience, 2014)
Feature selection is an important step in many pattern recognition systems aiming to overcome the so-called curse of
dimensionality. In this study, an optimized classification method was tested in 147 patients with major ...
Analysis of Brain Functional Changes in High-Frequency Repetitive Transcranial Magnetic Stimulation in Treatment-Resistant Depression
(Clinical EEG & Neuroscience, 2014)
Repetitive transcranial magnetic stimulation (rTMS) is a treatment procedure that uses magnetic fields to stimulate nerve cells in
the brain, and is associated with significant improvements in clinical symptoms of major ...
Predicting Dropout Student: An Application of Data Mining Methods in an Online Education Program
(2014)
This study examined the prediction of dropouts through data mining approaches in an online
program. The subject of the study was selected from a total of 189 students who registered to the
online Information Technologies ...
A Hybrid artificial intelligence method to classify trichotillomania and obsessive compulsive disorder
(2015-02)
Classification of psychiatric disorders is becoming one of the major focuses of research using artificial
intelligence approach. The combination of feature selection and classification methods generates
satisfactory ...