Cargando…
A new Graph Gaussian embedding method for analyzing the effects of cognitive training
Identifying heterogeneous cognitive impairment markers at an early stage is vital for Alzheimer’s disease diagnosis. However, due to complex and uncertain brain connectivity features in the cognitive domains, it remains challenging to quantify functional brain connectomic changes during non-pharmaco...
Autores principales: | Xu, Mengjia, Wang, Zhijiang, Zhang, Haifeng, Pantazis, Dimitrios, Wang, Huali, Li, Quanzheng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7524000/ https://www.ncbi.nlm.nih.gov/pubmed/32941425 http://dx.doi.org/10.1371/journal.pcbi.1008186 |
Ejemplares similares
-
Hyperbolic graph embedding of MEG brain networks to study brain alterations in individuals with subjective cognitive decline
por: Baker, Cole, et al.
Publicado: (2023) -
A randomized controlled trial of combined executive function and memory training on the cognitive and noncognitive function of individuals with mild cognitive impairment: Study rationale and protocol design
por: Zhang, Haifeng, et al.
Publicado: (2018) -
Embedding Learning with Triple Trustiness on Noisy Knowledge Graph
por: Zhao, Yu, et al.
Publicado: (2019) -
Computerized multi-domain cognitive training reduces brain atrophy in patients with amnestic mild cognitive impairment
por: Zhang, Haifeng, et al.
Publicado: (2019) -
Characterization of Brain Iron Deposition Pattern and Its Association With Genetic Risk Factor in Alzheimer’s Disease Using Susceptibility-Weighted Imaging
por: You, Peiting, et al.
Publicado: (2021)