Abstract: Alzheimer's disease (AD) is a progressive, irreversible brain illness that affects a person's thinking and causes the brain to shrink, eventually leading to death. It's required for the treatment of early stages of Alzheimer's disease in order to prevent further damage. Machine learning algorithms using various optimization and probabilistic methodologies can be used to make this diagnosis. Because no single non-amyloid protein has been proved to consistently diagnose Alzheimer's disease, using machine learning (ML) techniques to determine optimal combinations of non-amyloid proteins is a potential approach. As a result, our strategy is mostly dependent on machine learning in order to separate persons with normal brain ageing from those who are likely to develop Alzheimer's disease.
|
DOI:
10.17148/IJARCCE.2022.114164
