Identification of Subclinical Language Deficit Using Machine Learning Classification Based on Poststroke Functional Connectivity Derived from Low Frequency Oscillations

Post-stroke neuropsychological evaluation is time-intensive in assessing impairments in subjects without overt clinical deficits. We utilized functional connectivity (FC) from ten-minute non-invasive resting-state functional MRI (rs-fMRI) to identify stroke subjects at risk for subclinical language...

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Detalhes bibliográficos
Publicado no:Brain Connect
Main Authors: Mohanty, Rosaleena, Nair, Veena A., Tellapragada, Neelima, Williams, Leroy M., Kang, Theresa J., Prabhakaran, Vivek
Formato: Artigo
Idioma:Inglês
Publicado em: Mary Ann Liebert, Inc., publishers 2019
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Original Articles
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6445059/
https://ncbi.nlm.nih.gov/pubmed/30398379
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1089/brain.2018.0597
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