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Abstract #1960

Classification of AD, MCI and Controls Using Large-Scale Network Analysis

Gang Chen1, Barney Douglas Ward1, Chunming Xie1, Zhilin Wu1, Wenjun Li1, Jennifer Jones2, Malgorzata Franczak2, Piero Antuono2, Shi-Jiang Li1

1Department of Biophysics,, Medical College of Wisconsin, Milwaukee, WI, United States; 2Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States

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.