An empirical comparison of different approaches for combining multimodal neuroimaging data with Support Vector Machine

In the pursuit of clinical utility, neuroimaging researchers of psychiatric and neurological illness are increasingly using analyses, such as support vector machine (SVM), that allow inference at the single-subject level. Recent studies employing single-modality data, however, suggest that classific...

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Detaylı Bibliyografya
Asıl Yazarlar:	William ePettersson-Yeo, Stefania eBenetti, Andre F Marquand, Richard eJoules, Marco eCatani, Steve CR Williams, Paul eAllen, Philip eMcGuire, Andrea eMechelli
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	Frontiers Media S.A. 2014-07-01
Seri Bilgileri:	Frontiers in Neuroscience
Konular:	integration MRI psychosis label fusion Multi-kernel learning Support vector machine
Online Erişim:	http://journal.frontiersin.org/Journal/10.3389/fnins.2014.00189/full
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An empirical comparison of different approaches for combining multimodal neuroimaging data with Support Vector Machine

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