MRI-Based Alzheimer’s Diagnosis Using Machine Learning

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that poses a serious and increasing challenge to public health. This work summarizes AD by covering its risk factors, symptoms, diagnosis, treatment, and ongoing research. The main goal of managing AD is to reduce symptoms and improve the lives of affected individuals. This letter presents a systematic review that looks at predicting AD following the Preferred Reporting Item for Systematic Review and Meta-Analysis (PRISMA) guidelines. Alzheimer’s disease is a brain condition that worsens over time, gradually impairing memory and thinking skills, ultimately taking away individuals’ ability to perform even simple tasks on their own. As the main cause of dementia, Alzheimer’s represents a large majority of cases, impacting over 55 million people worldwide. To identify the biomarkers linked to Alzheimer’s, various scanning techniques are used. In the early stages of Alzheimer’s, changes in the brain’s chemical makeup have been linked to the macular area of the eye. Optical imaging is a rapidly growing field in medical research and clinical use. This technique offers a non-invasive way to visualize and diagnose various medical conditions. When paired with AI, it becomes a powerful tool for detecting Alzheimer’s in its early stages.