Based on resting-state fmri (rs-fMRI) data, this study aims to investigate the method of identifying AD and normal controls through the procedure of feature extraction and pattern recognition. We extracted the ALFF and ReHo parameters based on pre-processed resting-state fMRI data, and calculated some key parameters in graph theory through the functional connectivity network. Then the examination of the reliability of those features shows a satisfactory recognition rate of 94.4% to distinguish AD and normal controls.
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