On the Detection of Alzheimer's Disease using Naïve Bayes Classifier

Machine learning tools are increasingly employed for the early detection of various diseases over the last few years. This article makes a novel attempt in applying Naive Bayes classifier in discriminating healthy control from Alzheimer's affected brain. Percentage volumes of white matter (WM), gray matter (GM) and cerebro spinal fluid (CSF) are used as potential biomarkers in the proposed classification process. A large number of ADNI images have been considered for validating the results. Experimental observations have revealed satisfactory performance in terms of accuracy, sensitivity, precision and specificity of the classifier.