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P2‐447: Classification of AD, MCI and Controls Using Large‐Scale Network Analysis
Author(s) -
Chen Gang,
Ward B. Douglas,
Xie Chunming,
Wu Zhilin,
Jones Jennifer,
Franczak Malgorzata,
Antuono Piero,
Li Shi-Jiang
Publication year - 2010
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2010.08.021
Subject(s) - cognitive impairment , dementia , resting state fmri , audiology , medicine , pattern recognition (psychology) , mathematics , psychology , artificial intelligence , disease , neuroscience , computer science
There has been great interest in developing objective biologically based markers that can be used to predict risk, diagnose, stage, or track the course and treatment of dementia and other neurodegenerative diseases. Alzheimer disease (AD) is the most common form of dementia. Mild cognitive impairment (MCI) is a transitional state between normal aging and dementia, and is often considered a risk factor for AD. In this study, we employed resting-state MRI connectivity methods and the large-scale network analyses to discriminate between AD, MCI and healthy control subjects.