Paper Contents
Abstract
Alzheimer's disease is a neurodegenerative disorder that causes a progressive decline in cognitive function and memory loss. It is the most common cause of dementia in older adults, accounting for 60-80% of all dementia cases. The disease is characterized by the accumulation of abnormal protein deposits in the brain, including beta-amyloid plaques and tau protein tangles, which disrupt normal brain function and ultimately lead to the death of brain cells. The exact cause of Alzheimer's disease is not fully understood, but it is thought to be the result of a combination of genetic, environmental, and lifestyle factors. In this paper, we build a model to predict Alzheimers disease and know whether the person is cured, normal, or has Alzheimers Disease. By taking the dataset, preprocessing the dataset, and using Machine Learning Algorithms we classify whether the person comes under which category by considering the parameters such as group, number of visits, MR Delay, MMSE, Education, etc.
Copyright
Copyright © 2023 Farooq Sunar Mahammad. This is an open access article distributed under the Creative Commons Attribution License.
