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Publication Type : Journal Article
Publisher : J. Adv. Res. Dyn. Control Syst
Source : J. Adv. Res. Dyn. Control Syst, 9(6), pp.1368-1381.
Campus : Chennai
School : School of Engineering
Department : Computer Science and Engineering
Year : 2017
Abstract : Alzheimer's Disease (AD) or just Alzheimer's, is a neural condition of the human brain which is getting to be increasingly notorious for its chronic neurodegenerative capability to disorient the human mind and body completely. AD is getting to be more prevalent among the older people globally. Earlier, physical and mental assessments were the only gauge to find AD, but currently Magnetic Resonance Imaging (MRI), a valuable asset in medicine is getting to be increasingly effective in recognizing and diagnosing this disease. Various techniques have been found to help discern AD and " Mild Cognitive Impairment " (MCI), a brain function syndrome homogeneous to AD, but less severe.The proposed method utilizing a wrapper based feature selection technique for identifying a classification accuracy of an AD and then proposed Social Spider Metaheuristic is used to identify the significant features to diagnose an AD in effectively. Result shows the accuracy of the proposed technique.
Cite this Research Publication : Rajan, C. and Sountharrajan, S., 2017. Metaheuristic optimization technique for feature selection to detect the alzheimer disease from MRI. J. Adv. Res. Dyn. Control Syst, 9(6), pp.1368-1381.