Ant Colony Optimization Based Feature Selection Method for QEEG Data Classification - Test2 - elhamkhani - TriplyDB

Ant Colony Optimization Based Feature Selection Method for QEEG Data Classification

Ant Colony Optimization Based Feature Selection Method for QEEG Data Classification

http://www.wikidata.org/entity/Q30433209

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Ant colony optimization-based firewall anomaly mitigation engine.Classification of anti hepatitis peptides using Support Vector Machine with hybrid Ant Colony OptimizationThe Luxembourg database of trichothecene type B F. graminearum and F. culmorum producers

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Ant Colony Optimization Based Feature Selection Method for QEEG Data Classification

http://www.wikidata.org/entity/Q30433209

description

2014 nî lūn-bûn

@nan

2014 թուականի Յուլիսին հրատարակուած գիտական յօդուած

@hyw

2014 թվականի հուլիսին հրատարակված գիտական հոդված

@hy

2014年の論文

@ja

2014年論文

@yue

2014年論文

@zh-hant

2014年論文

@zh-hk

2014年論文

@zh-mo

2014年論文

@zh-tw

2014年论文

@wuu

name

Ant Colony Optimization Based Feature Selection Method for QEEG Data Classification

@ast

Ant Colony Optimization Based Feature Selection Method for QEEG Data Classification

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type

label

Ant Colony Optimization Based Feature Selection Method for QEEG Data Classification

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Ant Colony Optimization Based Feature Selection Method for QEEG Data Classification

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prefLabel

Ant Colony Optimization Based Feature Selection Method for QEEG Data Classification

@ast

Ant Colony Optimization Based Feature Selection Method for QEEG Data Classification

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PI.2014.11.3.243

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Psychiatry investigation

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Ant Colony Optimization Based Feature Selection Method for QEEG Data Classification

@en

P2093

Nevzat Tarhan

http://www.w3.org/2001/XMLSchema#string

Selahattin Gultekin

http://www.w3.org/2001/XMLSchema#string

Serhat Ozekes

http://www.w3.org/2001/XMLSchema#string

Turker Tekin Erguzel

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P2860

Neurophysiological predictors of non-response to rTMS in depression

The change of prefrontal QEEG theta cordance as a predictor of response to bupropion treatment in patients who had failed to respond to previous antidepressant treatments

Comparison of linear, nonlinear, and feature selection methods for EEG signal classification.

Diagnosis of psychiatric disorders using EEG data and employing a statistical decision model.

Efficacy and safety of transcranial magnetic stimulation in the acute treatment of major depression: a multisite randomized controlled trial.

Using pre-treatment electroencephalography data to predict response to transcranial magnetic stimulation therapy for major depression.

A review of feature selection techniques in bioinformatics.

Patterns of response to repetitive transcranial magnetic stimulation (rTMS) in major depression: replication study in drug-free patients.

A pilot study to determine whether machine learning methodologies using pre-treatment electroencephalography can predict the symptomatic response to clozapine therapy.

Quantitative spectral analysis of EEG in psychiatry revisited: drawing signs out of numbers in a clinical setting.

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243-250

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scholarly article

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10.4306/PI.2014.11.3.243

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3

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11

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2014-07-21T00:00:00Z

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264628506

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25110496

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4124182

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