Comparative Analysis of Machine Learning Algorithms on Prediction of Alzheimer from MRI

Alzheimer's Disease (AD) is a well-recognized cause of dementia among the elderly population, affecting an increasing number of individuals. The origins and progression mechanisms of AD remain intricate and not yet fully comprehended. Magnetic Resonance Imaging (MRI) is a neuroimaging technique that enables in-depth and precise investigations of the disease, providing a valuable tool for both diagnosis and early detection of AD. However, handling extensive sets of clinical images poses a significant challenge, prompting researchers to explore machine learning methods. Machine learning encompasses a range of computer-assisted techniques that adapt their outcomes toward predefined objectives. This study incorporates various machine learning techniques and conducts a comparative analysis to determine the most effective approach for Alzheimer's Disease detection. Additionally, a web application has been developed, enabling physicians to predict a patient's condition automatically.