Cargando…
Aberrated Multidimensional EEG Characteristics in Patients with Generalized Anxiety Disorder: A Machine-Learning Based Analysis Framework
Although increasing evidences support the notion that psychiatric disorders are associated with abnormal communication between brain regions, scattered studies have investigated brain electrophysiological disconnectivity of patients with generalized anxiety disorder (GAD). To this end, this study in...
Autores principales: | Shen, Zhongxia, Li, Gang, Fang, Jiaqi, Zhong, Hongyang, Wang, Jie, Sun, Yu, Shen, Xinhua |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320264/ https://www.ncbi.nlm.nih.gov/pubmed/35891100 http://dx.doi.org/10.3390/s22145420 |
Ejemplares similares
-
Machine Learning Techniques Reveal Aberrated Multidimensional EEG Characteristics in Patients with Depression
por: Li, Gang, et al.
Publicado: (2023) -
Difference analysis of multidimensional electroencephalogram characteristics between young and old patients with generalized anxiety disorder
por: Wang, Jie, et al.
Publicado: (2022) -
Aberrant amplitude low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) in generalized anxiety disorder (GAD) and their roles in predicting treatment remission
por: Shen, Zhongxia, et al.
Publicado: (2020) -
Combining S100B and Cytokines as Neuro-Inflammatory Biomarkers for Diagnosing Generalized Anxiety Disorder: A Proof-of-Concept Study Based on Machine Learning
por: Shen, Zhongxia, et al.
Publicado: (2022) -
Multidimensional hyperspin machine
por: Calvanese Strinati, Marcello, et al.
Publicado: (2022)