International Journal of Engineering and Technology

The accurate diagnosis of Alzheimer's diseases (AD) and prodromal stage like Mild Cognitive Impairment (MCI) play a vital role in preventing progression of Alzheimer diseases and mild cognitive impairment. In view of that, a multi-kernel classifier model with noninvasive imaging technique for AD/MCI patients is proposed in this paper. The proposed model includes four techniques, such as PCA, Stability Selection, Multitask deep models with dropout and AD/MCI diagnosis with kernel SVM leads into the deep learning framework. Also, the proposed approach is evaluated with real-world ADNI datasets (Alzheimer's diseases Neuroimaging Initiative) and its results are analyzed.