ALZHEIMER’S DISEASE DETECTION USING KRILL HERD FEATURE SELECTION WITH NB, KNN AND CART CLASSIFIER

Alzheimer's disease (AD) is the most common type of dementia and a major cause of disability worldwide. It is a progressive and degenerative disease that affects brain cells and its early diagnosis has been essential for appropriate intervention by health professionals. Magnetic Resonance Imaging (MRI) is a non-invasive medical imaging technique used in radiology to visualize detailed internal structure and limited functions of the body. Feature selection is one of the best optimization problems in human recognition, which reduces the number of features, removes noise and redundant data in images, and results in high rate of recognition. In this work, Krill Herd (KH) based feature selection methods are proposed. The NB, KNN and CART classifier is used. Experiments show the effectiveness of the proposed technique.