JointMMCC: joint maximum-margin classification and clustering of imaging data. - Test2 - elhamkhani - TriplyDB

JointMMCC: joint maximum-margin classification and clustering of imaging data.

JointMMCC: joint maximum-margin classification and clustering of imaging data.

http://www.wikidata.org/entity/Q34157017

about

Beyond Lumping and Splitting: A Review of Computational Approaches for Stratifying Psychiatric Disorders Neural signatures of autism spectrum disorders: insights into brain network dynamics Capturing heterogeneous group differences using mixture-of-experts: Application to a study of aging.Heterogeneity of structural brain changes in subtypes of schizophrenia revealed using magnetic resonance imaging pattern analysis.HYDRA: Revealing heterogeneity of imaging and genetic patterns through a multiple max-margin discriminative analysis framework.Detecting neuroimaging biomarkers for schizophrenia: a meta-analysis of multivariate pattern recognition studies Consensus clustering approach to group brain connectivity matrices.Disentangling Disease Heterogeneity with Max-Margin Multiple Hyperplane Classifier Investigating the Correspondence of Clinical Diagnostic Grouping With Underlying Neurobiological and Phenotypic Clusters Using Unsupervised Machine Learning

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P2860

JointMMCC: joint maximum-margin classification and clustering of imaging data.

http://www.wikidata.org/entity/Q34157017

description

2012 nî lūn-bûn

@nan

2012 թուականի Փետրուարին հրատարակուած գիտական յօդուած

@hyw

2012 թվականի փետրվարին հրատարակված գիտական հոդված

@hy

2012年の論文

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2012年論文

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2012年論文

@zh-hant

2012年論文

@zh-hk

2012年論文

@zh-mo

2012年論文

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2012年论文

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name

JointMMCC: joint maximum-margin classification and clustering of imaging data.

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JointMMCC: joint maximum-margin classification and clustering of imaging data.

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JointMMCC: joint maximum-margin classification and clustering of imaging data.

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type

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JointMMCC: joint maximum-margin classification and clustering of imaging data.

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JointMMCC: joint maximum-margin classification and clustering of imaging data.

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JointMMCC: joint maximum-margin classification and clustering of imaging data.

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JointMMCC: joint maximum-margin classification and clustering of imaging data.

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JointMMCC: joint maximum-margin classification and clustering of imaging data.

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JointMMCC: joint maximum-margin classification and clustering of imaging data.

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TMI.2012.2186977

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IEEE Transactions on Medical Imaging

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JointMMCC: joint maximum-margin classification and clustering of imaging data.

@en

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Roman Filipovych

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Susan M Resnick

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The bipolar disorder risk allele at CACNA1C also confers risk of recurrent major depression and of schizophrenia

Semi-supervised cluster analysis of imaging data

Spatial patterns of brain atrophy in MCI patients, identified via high-dimensional pattern classification, predict subsequent cognitive decline

“Mini-mental state”

Gene-wide analyses of genome-wide association data sets: evidence for multiple common risk alleles for schizophrenia and bipolar disorder and for overlap in genetic risk

Structural and functional biomarkers of prodromal Alzheimer's disease: a high-dimensional pattern classification study.

Alzheimer disease: quantitative structural neuroimaging for detection and prediction of clinical and structural changes in mild cognitive impairment

Computer aided diagnosis system for the Alzheimer's disease based on partial least squares and random forest SPECT image classification.

Longitudinal cognitive decline is associated with fibrillar amyloid-beta measured by [11C]PiB

The external validity of Asperger disorder: lack of evidence from the domain of neuropsychology.

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1124-1140

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scholarly article

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10.1109/TMI.2012.2186977

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5

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31

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Christos Davatzikos

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2012-02-06T00:00:00Z

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221826516

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3386308

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