Abstract
The brain is one of the most sensitive parts of the human body which
transmits millions of signals every moment. Dementia is the most emerging brain
health issue which involves memory loss, difficulty in problem-solving, handling
complex tasks, etc. Dementia is a syndrome that causes a loss of mental ability. It
affects memory, thinking, shape, comprehension, counting, reading ability, language,
and judgment. Dementia affects millions of people and can be the leading cause of
death. It is now the seventh leading cause of death worldwide, as well as one of the
major causes of impairment and reliance on elderly people. There is no treatment for
dementia at present. The importance of early detection and diagnosis in improving
early and effective management is crucial. Predicting dementia in advance can lead us
to a better life. To predict dementia, various Machine Learning models have been used.
In this paper, Dementia is predicted on the basis of MRI Images, for this, three
different datasets of MRI Images have been collected. Furthermore, for better
prediction, various Machine learning models are used to predict dementia and validate
the performance with statistical analysis like K-Nearest Neighbours, XG Boost,
Support Vector Machine, Random Forest Algorithm (RFA), and Convolutional Neural
Network (CNN). Out of all algorithms, Random Forest Algorithm and Convolutional
Neural Network gave the best result with the accuracy of 93.2 and 99.9 respectively.