A pilot study to determine whether machine learning methodologies using pre-treatment electroencephalography can predict the symptomatic response to clozapine therapy.
about
Towards the identification of imaging biomarkers in schizophrenia, using multivariate pattern classification at a single-subject levelClozapine Monitoring in Clinical Practice: Beyond the Mandatory RequirementMusical experience, plasticity, and maturation: issues in measuring developmental change using EEG and MEG.Ant Colony Optimization Based Feature Selection Method for QEEG Data ClassificationNeuroimaging-based biomarkers in psychiatry: clinical opportunities of a paradigm shift.EEG machine learning for accurate detection of cholinergic intervention and Alzheimer's disease.Novel machine learning methods for ERP analysis: a validation from research on infants at risk for autism.Clozapine response and pre-treatment EEG-is there some kind of relationshipA wavelet-based technique to predict treatment outcome for Major Depressive DisorderFactors associated with response to clozapine in schizophrenia: a review.Realising stratified psychiatry using multidimensional signatures and trajectories.Resting-state cortical connectivity predicts motor skill acquisition.Electroencephalography and analgesics.A review of recent literature employing electroencephalographic techniques to study the pathophysiology, phenomenology, and treatment response of schizophrenia.The role of machine learning in neuroimaging for drug discovery and development.A systematic review on the impact of psychotropic drugs on electroencephalogram waveforms in psychiatry.Machine learning on encephalographic activity may predict opioid analgesia.F-ratio test and hypothesis weighting: a methodology to optimize feature vector size.Feature Selection and Classification of Electroencephalographic Signals: An Artificial Neural Network and Genetic Algorithm Based Approach.Biological Predictors of Clozapine Response: A Systematic ReviewPredicting methylphenidate response in attention deficit hyperactivity disorder: A preliminary study
P2860
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P2860
A pilot study to determine whether machine learning methodologies using pre-treatment electroencephalography can predict the symptomatic response to clozapine therapy.
description
2010 nî lūn-bûn
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2010年の論文
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2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
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2010年论文
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2010年论文
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2010年论文
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name
A pilot study to determine whe ...... response to clozapine therapy.
@en
A pilot study to determine whe ...... response to clozapine therapy.
@nl
type
label
A pilot study to determine whe ...... response to clozapine therapy.
@en
A pilot study to determine whe ...... response to clozapine therapy.
@nl
prefLabel
A pilot study to determine whe ...... response to clozapine therapy.
@en
A pilot study to determine whe ...... response to clozapine therapy.
@nl
P2093
P1476
A pilot study to determine whe ...... response to clozapine therapy.
@en
P2093
Ahmad Khodayari-Rostamabad
Duncan J Maccrimmon
Gary M Hasey
Hubert de Bruin
James P Reilly
P304
P356
10.1016/J.CLINPH.2010.05.009
P577
2010-06-17T00:00:00Z