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Artificial Intelligence and Machine Learning Models for Alzheimer's Disease
Abstract
Alzheimer's disease is a brain disorder that slowly destroys memory and thinking skills and, eventually, the ability to carry out the simplest tasks. In most people with the disease, those with the late-onset type symptoms first appear in their mid-60s. Early-onset Alzheimer's occurs between a person's 30s and mid-60s and is very rare. Alzheimer's disease is the most common cause of dementia among older adults. Early diagnosis of Alzheimer's disease is essential for the progress of more prevailing treatments. Machine learning (ML), a branch of artificial intelligence, employs a variety of probabilistic and optimization techniques that permits PCs to gain from vast and complex datasets. As a result, researchers focus on using machine learning frequently for diagnosis of early stages of Alzheimer's disease. This project presents a review, analysis and critical evaluation of the recent work done for the early detection of Alzheimer's disease using ML techniques.
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