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Abstract #2353

Prediction of early stage of AD based on functional connectivity network characteristics: an fMRI-based study

Zhizheng Zhuo1,2, Zhuqing Long1, Bin Jing1, Xiangyu Ma1, Han Liu1, Jianxin Dong1, Xiao Mo1, Qi Yan1, and Haiyun Li1

1Bio-medical Engineering, Capital Medical University, Beijing, People's Republic of China, 2Clinical Science, Philips Healthcare, Beijing, People's Republic of China

MCI (Mild Cognitive Impairment) is a pre-stage of Alzheimer’s Disease (AD). And the early detection of MCI is important for early treatment of AD patients. In this work, prediction efficiency of early stage of AD based on the functional connectivity network characteristics was evaluated by using a couple of classifiers with AAL_90 and AAL_1024 templates. The results showed that brain functional characteristics were effective in the prediction of MCI with a SVM-based classifier. And a more fine template could improve prediction accuracy.

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