@article{MAKHILLAJIT20201976798,
    title = {A Novel Approach to Alzheimer’s Disease Stage Classification using Supervised Learning
Approach},
    journal = {Asian Journal of Information Technology},
    volume = {19},
    number = {7},
    pages = {137-141},
    year = {2020},
    issn = {1682-3915},
    doi = {ajit.2020.137.141},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2020.137.141},
    author = {Shaik and},
    keywords = {Support vector machines,gray level co-occurrence matrix,Alzheimer’s,dementia,Naive Bayes classifier,kNN},
    abstract = {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.}
    }