fMRI data classification based on SVM and its application in diagnosis of MCI

To improve the quality of early diagnosis of MCI(mild cognitive impairment)effectively,a data classification method based on SVM(support vector machine)is presented and a ensemble classifier with higher classification accuracy is constructed.The traditional MCI diagnosis processes have long inspection cycles and high subjective errors.To achieve the data mining,the SVM data classification method is proposed.The feature is extracted from each voxel for the classification of fMRI images.Then,the distribution of the voxels with higher classification accuracy is analyzed.Finally,the ensemble classifier is constructed by using weighted means method so as to assist in the clinical diagnosis better.