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Complex network analysis of resting state EEG in amnestic mild cognitive impairment patients with type 2 diabetes
Purpose: Diabetes is a great risk factor for dementia and mild cognitive impairment (MCI). This study investigates whether complex network-derived features in resting state EEG (rsEEG) could be applied as a biomarker to distinguish amnestic mild cognitive impairment (aMCI) from normal cognitive func...
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| Publicado no: | Front Comput Neurosci |
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| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Frontiers Media S.A.
2015
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4624867/ https://ncbi.nlm.nih.gov/pubmed/26578946 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fncom.2015.00133 |
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