Automatic Bayesian classification of healthy controls, bipolar disorder, and schizophrenia using intrinsic connectivity maps from FMRI data.
about
A momentary biomarker for depressive moodMultivariate classification of blood oxygen level-dependent FMRI data with diagnostic intention: a clinical perspectiveADHD-200 Global Competition: diagnosing ADHD using personal characteristic data can outperform resting state fMRI measurements.Fusion analysis of functional MRI data for classification of individuals based on patterns of activation.Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls.High classification accuracy for schizophrenia with rest and task FMRI data.Long-term treatment of bipolar disorder with a radioelectric asymmetric conveyor.Identify schizophrenia using resting-state functional connectivity: an exploratory research and analysis.Individualized identification of euthymic bipolar disorder using the Cambridge Neuropsychological Test Automated Battery (CANTAB) and machine learning.Amygdala functional connectivity predicts pharmacotherapy outcome in pediatric bipolar disorderMultimodal Neuroimaging-Informed Clinical Applications in Neuropsychiatric Disorders.Co-altered functional networks and brain structure in unmedicated patients with bipolar and major depressive disorders.Machine learning of structural magnetic resonance imaging predicts psychopathic traits in adolescent offenders.On the use and misuse of genomic and neuroimaging science in forensic psychiatry: current roles and future directionsClassification of schizophrenia and bipolar patients using static and dynamic resting-state fMRI brain connectivityClassification of schizophrenia patients based on resting-state functional network connectivity.A Hierarchical Bayesian Model for the Identification of PET Markers Associated to the Prediction of Surgical Outcome after Anterior Temporal Lobe Resection.Advances in clinical neuroimaging: implications for autism spectrum disorders.Classification and Prediction of Brain Disorders Using Functional Connectivity: Promising but Challenging
P2860
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P2860
Automatic Bayesian classification of healthy controls, bipolar disorder, and schizophrenia using intrinsic connectivity maps from FMRI data.
description
2010 nî lūn-bûn
@nan
2010 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած
@hyw
2010 թվականի սեպտեմբերին հրատարակված գիտական հոդված
@hy
2010年の論文
@ja
2010年学术文章
@wuu
2010年学术文章
@zh-cn
2010年学术文章
@zh-hans
2010年学术文章
@zh-my
2010年学术文章
@zh-sg
2010年學術文章
@yue
name
Automatic Bayesian classificat ...... nectivity maps from FMRI data.
@ast
Automatic Bayesian classificat ...... nectivity maps from FMRI data.
@en
type
label
Automatic Bayesian classificat ...... nectivity maps from FMRI data.
@ast
Automatic Bayesian classificat ...... nectivity maps from FMRI data.
@en
prefLabel
Automatic Bayesian classificat ...... nectivity maps from FMRI data.
@ast
Automatic Bayesian classificat ...... nectivity maps from FMRI data.
@en
P2860
P50
P921
P1476
Automatic Bayesian classificat ...... nectivity maps from FMRI data.
@en
P2860
P304
P356
10.1109/TBME.2010.2080679
P577
2010-09-27T00:00:00Z