Abstrait

AD classification based on brain functional network using ADNI

Jie Xiang, Hong Liang, Cao Rui, Zheng Wu, Junjie Chen

In order to assist the diagnosis of mild cognitive impairment (MCI) and provide a new diagnostic method, resting state brain functional networks of early mild cognitive impairment, late mild cognitive impairment and normal controls are constructed, node attributes of brain functional networks based on complex network are calculated and differences between groups are analyzed which served as the classification features. Then, the subjects are classified using support vector machine algorithm. The experimental result showed that this method can be used for diagnosis of MCI, having a certain application value