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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Detalles Bibliográficos
Autores principales: Wang, Yanlu, Li, Tie-Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4424860/
https://www.ncbi.nlm.nih.gov/pubmed/26005413
http://dx.doi.org/10.3389/fnhum.2015.00259

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4424860/
https://www.ncbi.nlm.nih.gov/pubmed/26005413
http://dx.doi.org/10.3389/fnhum.2015.00259

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