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Dimensionality of ICA in resting-state fMRI investigated by feature optimized classification of independent components with SVM

Different machine learning algorithms have recently been used for assisting automated classification of independent component analysis (ICA) results from resting-state fMRI data. The success of this approach relies on identification of artifact components and meaningful functional networks. A limiti...

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Опубликовано в: :Front Hum Neurosci
Главные авторы: Wang, Yanlu, Li, Tie-Qiang
Формат: Artigo
Язык:Inglês
Опубликовано: Frontiers Media S.A. 2015
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Online-ссылка:https://ncbi.nlm.nih.gov/pmc/articles/PMC4424860/
https://ncbi.nlm.nih.gov/pubmed/26005413
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnhum.2015.00259
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