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Learning Brain Connectivity Sub-networks by Group- Constrained Sparse Inverse Covariance Estimation for Alzheimer's Disease Classification

Background/Aims: Brain functional connectivity networks constructed from resting-state functional magnetic resonance imaging (rs-fMRI) have been widely used for classifying Alzheimer's disease (AD) from normal controls (NC). However, conventional correlation analysis methods only capture the pa...

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Detalles Bibliográficos
Autores principales:	Li, Yang, Liu, Jingyu, Huang, Jie, Li, Zuoyong, Liang, Peipeng
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2018
Materias:	Neuroscience
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6143825/ https://www.ncbi.nlm.nih.gov/pubmed/30258358 http://dx.doi.org/10.3389/fninf.2018.00058

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