Detection of cognitive impairment using a machine-learning algorithm [Corrigendum]
Youn YC, Choi SH, Shin HW, et al. Neuropsychiatr Dis Treat. 2018;14:2939–2945.On page 2944, under Supplementary materials section, the Table S2 was incorrect.Read the original article.
Guardado en:
Autores principales: | Youn YC, Choi SH, Shin HW, Kim KW, Jang JW, Jung JJ, Hsiung GY, Kim SY |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Dove Medical Press
2019
|
Materias: | |
Acceso en línea: | https://doaj.org/article/26917275e11742fcad37df8c74e8145e |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Detection of cognitive impairment using a machine-learning algorithm
por: Youn YC, et al.
Publicado: (2018) -
Effect of 12-week home-based cognitive training on cognitive function and brain metabolism in patients with amnestic mild cognitive impairment
por: Park J, et al.
Publicado: (2019) -
Power Spectral Changes of Quantitative EEG in the Subjective Cognitive Decline: Comparison of Community Normal Control Groups
por: Jeong HT, et al.
Publicado: (2021) -
11C-PIB PET imaging reveals that amyloid deposition in cases with early-onset Alzheimer’s disease in the absence of known mutations retains higher levels of PIB in the basal ganglia
por: Youn YC, et al.
Publicado: (2017) -
Reversion From Mild Cognitive Impairment To Normal Cognition: False-Positive Error Or True Restoration Thanks To Cognitive Control Ability?
por: Chung JY, et al.
Publicado: (2019)