Machine learning classification of resting state functional connectivity predicts smoking status

Machine learning-based approaches are now able to examine functional magnetic resonance imaging data in a multivariate manner and extract features predictive of group membership. We applied support vector machine (SVM)-based classification to resting state functional connectivity (rsFC) data from ni...

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Detalles Bibliográficos
Autores principales: Pariyadath, Vani, Stein, Elliot A., Ross, Thomas J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2014
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4058899/
https://www.ncbi.nlm.nih.gov/pubmed/24982629
http://dx.doi.org/10.3389/fnhum.2014.00425

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4058899/
https://www.ncbi.nlm.nih.gov/pubmed/24982629
http://dx.doi.org/10.3389/fnhum.2014.00425

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