Alzheimer's Disease is the most common type of dementia disease affecting millions of people across the globe. It involves degeneration of the brain which is irreversible and gradually ends up with the complete brain failure. This book presents a supervised learning model to effectively capture the complex feature interactions, in the sample space of Alzheimer's Disease data, for knowledge discovery. The discovered knowledge is further used to quantify the similarity of a test subject to the demented class. The outcome of the work clearly demonstrates that, supervised learning model can be used effectively to quantify the severity of of Alzheimer's Disease on a standard measurable scale. This scale of distance can be used as a supplement for Clinical Dementia Rating.

C. R. Aditya is an Assistant Professor of Computer Science & Engineering. He specializes in developing Learning Models for detecting Neurological Disorders. Sanjay Pande M. B. is a professor of Computer Science & Engineering and a senior researcher in the field of Pattern recognition and Medical Informatics.