TY  - JOUR
T1  - A Novel Approach to Alzheimer’s Disease Stage Classification using Supervised Learning
Approach
AU - Basheera, Shaik AU - SatyaSai Ram, M. 
JO  - Asian Journal of Information Technology
VL  - 19
IS  - 7
SP  - 137
EP  - 141
PY  - 2020
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2020.137.141
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2020.137.141
KW  - Support vector machines
KW  -gray level co-occurrence matrix
KW  -Alzheimer’s
KW  -dementia
KW  -Naive Bayes classifier
KW  -kNN
AB  - Medical imaging playsa major role in diagnosis
of diseases, machine learning play major role in diagnosis
of medical images using computer-aided diagnosis. As
India’s urban population is goon increasing Neurological
disorders also increases, Alzheimer’s is one of the major
dementia of neurons and make the death tally as high next
to cancer. Estimating the stage of the Alzheimer’s is a
challenging task. We use T2 Weighted Brain MRI and
Extract the Texture Features from those images. Train the
classifier and perform crossover validation using those
features. Support Vector Machines (SVM) give the good
classification accuracy than comparing to the Naïve Bayes
classifier and KNN. Test the classifiers with unknown
images. The result is compared with clinical information
SVM gives 100% accuracy.
ER  -