Prognostic and diagnostic potential of the structural neuroanatomy of depression.
about
Studying depression using imaging and machine learning methodsBiological predictors of pharmacological therapy in anxiety disordersBrain Functional Effects of Psychopharmacological Treatment in Major Depression: a Focus on Neural Circuitry of Affective ProcessingBrain Structural Effects of Antidepressant Treatment in Major DepressionMultivariate pattern recognition for diagnosis and prognosis in clinical neuroimaging: state of the art, current challenges and future trendsA review of feature reduction techniques in neuroimagingDiagnostic potential of structural neuroimaging for depression from a multi-ethnic community sample.Predictive classification of individual magnetic resonance imaging scans from children and adolescents.Neuroimaging-based biomarkers in psychiatry: clinical opportunities of a paradigm shift.Neuroimaging for psychotherapy research: current trendsDiagnostic classification of specific phobia subtypes using structural MRI data: a machine-learning approach.A MRS study of metabolic alterations in the frontal white matter of major depressive disorder patients with the treatment of SSRIsIncreased cortical-limbic anatomical network connectivity in major depression revealed by diffusion tensor imagingPattern of neural responses to verbal fluency shows diagnostic specificity for schizophrenia and bipolar disorderDiagnosis of autism spectrum disorders using regional and interregional morphological features.Resting-state functional connectivity abnormalities in first-onset unmedicated depression.Diagnostic and therapeutic utility of neuroimaging in depression: an overviewBiomarkers to predict antidepressant responseClassification of different therapeutic responses of major depressive disorder with multivariate pattern analysis method based on structural MR scans.Prefrontal cortical abnormalities in currently depressed versus currently remitted patients with major depressive disorder.Towards automated detection of depression from brain structural magnetic resonance images.Frontocingulate dysfunction in depression: toward biomarkers of treatment response.Automated hippocampal shape analysis predicts the onset of dementia in mild cognitive impairment.Sparse network-based models for patient classification using fMRI.Fusion analysis of first episode depression: where brain shape deformations meet local composition of tissue.Clinical prediction from structural brain MRI scans: a large-scale empirical study.Prediction of pediatric unipolar depression using multiple neuromorphometric measurements: a pattern classification approach.Neuroimaging-based methods for autism identification: a possible translational application?Subregional hippocampal deformations in major depressive disorderModulatory effects of brain-derived neurotrophic factor Val66Met polymorphism on prefrontal regions in major depressive disorder.Predicting the Naturalistic Course of Major Depressive Disorder Using Clinical and Multimodal Neuroimaging Information: A Multivariate Pattern Recognition StudyStructural MRI-Based Predictions in Patients with Treatment-Refractory Depression (TRD).Identifying predictors, moderators, and mediators of antidepressant response in major depressive disorder: neuroimaging approaches.Control-group feature normalization for multivariate pattern analysis of structural MRI data using the support vector machine.A Prospective, Longitudinal Study of the Effect of Remission on Cortical Thickness and Hippocampal Volume in Patients with Treatment-Resistant Depression.Diagnostic neuroimaging across diseases.Classification of brain disease in magnetic resonance images using two-stage local feature fusionSeparating generalized anxiety disorder from major depression using clinical, hormonal, and structural MRI data: A multimodal machine learning study.Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction.Clinical application of brain imaging for the diagnosis of mood disorders: the current state of play.
P2860
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P2860
Prognostic and diagnostic potential of the structural neuroanatomy of depression.
description
2009 nî lūn-bûn
@nan
2009 թուականի Յուլիսին հրատարակուած գիտական յօդուած
@hyw
2009 թվականի հուլիսին հրատարակված գիտական հոդված
@hy
2009年の論文
@ja
2009年論文
@yue
2009年論文
@zh-hant
2009年論文
@zh-hk
2009年論文
@zh-mo
2009年論文
@zh-tw
2009年论文
@wuu
name
Prognostic and diagnostic potential of the structural neuroanatomy of depression.
@ast
Prognostic and diagnostic potential of the structural neuroanatomy of depression.
@en
Prognostic and diagnostic potential of the structural neuroanatomy of depression.
@en-gb
type
label
Prognostic and diagnostic potential of the structural neuroanatomy of depression.
@ast
Prognostic and diagnostic potential of the structural neuroanatomy of depression.
@en
Prognostic and diagnostic potential of the structural neuroanatomy of depression.
@en-gb
prefLabel
Prognostic and diagnostic potential of the structural neuroanatomy of depression.
@ast
Prognostic and diagnostic potential of the structural neuroanatomy of depression.
@en
Prognostic and diagnostic potential of the structural neuroanatomy of depression.
@en-gb
P2093
P2860
P1433
P1476
Prognostic and diagnostic potential of the structural neuroanatomy of depression.
@en
P2093
Carlton Chu
Cynthia H Y Fu
Sergi G Costafreda
P2860
P356
10.1371/JOURNAL.PONE.0006353
P407
P577
2009-07-27T00:00:00Z