Cargando…
Dynamic functional network connectivity discriminates mild traumatic brain injury through machine learning
Mild traumatic brain injury (mTBI) can result in symptoms that affect a person's cognitive and social abilities. Improvements in diagnostic methodologies are necessary given that current clinical techniques have limited accuracy and are solely based on self-reports. Recently, resting state func...
Autores principales: | Vergara, Victor M., Mayer, Andrew R., Kiehl, Kent A., Calhoun, Vince D. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6051314/ https://www.ncbi.nlm.nih.gov/pubmed/30034999 http://dx.doi.org/10.1016/j.nicl.2018.03.017 |
Ejemplares similares
-
The effect of preprocessing in dynamic functional network connectivity used to classify mild traumatic brain injury
por: Vergara, Victor M., et al.
Publicado: (2017) -
Functional outcome is tied to dynamic brain states after mild to moderate traumatic brain injury
por: van der Horn, Harm J., et al.
Publicado: (2019) -
Resting-state fMRI dynamic functional network connectivity and associations with psychopathy traits
por: Espinoza, Flor A., et al.
Publicado: (2019) -
Low-frequency connectivity is associated with mild traumatic brain injury
por: Dunkley, B.T., et al.
Publicado: (2015) -
Machine learning classification of chronic traumatic brain injury using diffusion tensor imaging and NODDI: A replication and extension study
por: Maurer, J. Michael, et al.
Publicado: (2023)