An Early Prediction and Detection of Alzheimer's Disease

Computer Engineering

One of the main worries recently has been Alzheimer's illness. This illness affects over 45 million people worldwide. Alzheimer's is a degenerative brain illness that primarily affects older people and has an unknown cause and pathogenesis. Dementia, which gradually kills brain cells, is the primary cause of Alzheimer's disease. This illness caused people to lose their capacity for thought, reading, and many other things. By foreseeing the disease, a machine learning system can mitigate this issue. The major goal is to identify dementia in a variety of people. The findings and analysis from multiple machine learning models used to identify dementia are presented in this research. The system was created using the Open Access Series of Imaging Studies (OASIS) dataset. Despite being modest, the dataset is small Several machine learning models have used and studied. . Prediction techniques include support vector machines, logistic regression, decision trees, and random forests. The system has been used both with and without fine-tuning. When the results are compared, it is discovered that the support vector machine produces the best outcomes of all the models. Among many patients, it is the most accurate at spotting dementia. among them, dementia. Even though there are many machine learning systems, their results are often inconsistent and wrong. They also struggle with concerns of overfitting and underfitting. So, using machine learning to assist medical technicians, we have developed a model that can detect Alzheimer's disease early. It will confirm and demonstrate whether or not someone has Alzheimer's disease

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