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...

Descripción completa

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

Internet

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

Ejemplares similares