Machine Learning Approaches for Predicting Early-Stage Alzheimer's Disease

The primary cause of dementia in older adults is Alzheimer's disease (AD). Nowadays, there is a lot of focus on using machine learning to detect metabolic diseases that impact many people globally, such as diabetes and Alzheimer's. Every year, the occurrence rates rise at an astonishing amount. There are neurodegenerative fluctuations in the brain associated with Alzheimer's disease. A growing number of people, their families, and the healthcare system will be affected by diseases that hamper memory and functioning as our aging population grows. On the social, financial, and economic fronts, these consequences will be significant. Alzheimer's disease is unpredictable when it is first developing. Early AD treatment is more beneficial and results in less minor damage than a later treatment. This study aims to contribute to the field by exploring machine learning models for the early-stage prediction of Alzheimer's Disease, providing a more efficient and accurate approach to diagnosis.