Alzheimer Disease Detection on Mri Scans Using Machine Learning Techniques

Abstract

The brain is one of the most important organs of the human body and is involved in important functions of the human body. Many types of brain disease Alzheimer's disease is one of them. It’s a very harmful and long-term illness. AD is a progressive neurological disorder. There is no cure for this disease, but early diagnosis and regular and correct treatment allow patients to lead a normal life. The disease is common in people who are under extreme stress and have been studying for a long time. The disease is more common in middle-class countries, but it is increasing in today's high-income countries. The immune system of patients with this disease gradually deteriorates, and as a result, patients suffer from a wide variety of complex illnesses. In this dataset, 400 brains were scanned by MRI scans. Using measurements from different parts of the brain of 165 people, we predict how accurately a person will develop AD through several machine learning algorithms. ML is a simple approach that can be used to determine a person's current state without human help. Due to the advantages of this approach, ML is very popular. This paper uses scans the brain via MRI and uses the score of the part that causes AD to identify whether a person with AD is infected via the Machine Learning approach. This paper details the machine learning model to be monitored.