Cargando…
Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks
Neuroimaging in combination with graph theory has been successful in analyzing the functional connectome. However almost all analysis are performed based on static graph theory. The derived quantitative graph measures can only describe a snap shot of the disease over time. Neurodegenerative disease...
Autores principales: | Meyer-Bäse, Anke, Roberts, Rodney G., Illan, Ignacio A., Meyer-Bäse, Uwe, Lobbes, Marc, Stadlbauer, Andreas, Pinker-Domenig, Katja |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5633615/ https://www.ncbi.nlm.nih.gov/pubmed/29051730 http://dx.doi.org/10.3389/fncom.2017.00087 |
Ejemplares similares
-
AI‐Enhanced Diagnosis of Challenging Lesions in Breast MRI: A Methodology and Application Primer
por: Meyer‐Base, Anke, et al.
Publicado: (2020) -
Current Status and Future Perspectives of Artificial Intelligence in Magnetic Resonance Breast Imaging
por: Meyer-Bäse, Anke, et al.
Publicado: (2020) -
Spatial component analysis of MRI data for Alzheimer's disease diagnosis: a Bayesian network approach
por: Illan, Ignacio A., et al.
Publicado: (2014) -
Artificial Intelligence in Oncology: A Topical Collection in 2022
por: Stadlbauer, Andreas, et al.
Publicado: (2023) -
Determining and interpreting correlations in lipidomic networks found in glioblastoma cells
por: Görke, Robert, et al.
Publicado: (2010)