Alzheimer’s Disease (AD) affects millions worldwide, with cases expected to rise from 36 million today to over 100 million by 2050. Given the limited treatment options, early detection and intervention are crucial. Our project utilizes the UK Biobank’s extensive datasets, including brain images and genetic data, combined with health assessments such as cognitive scores and lifestyle factors, to uncover early signs of Alzheimer’s and factors influencing its progression. Over the next three years, we will use advanced statistical and machine learning techniques to: 1. Identify individuals at high risk of developing Alzheimer’s. 2. Investigate how changes in brain structure and function correlate with cognitive decline. Create predictive models for Alzheimer’s progression and risk assessment. Our research aims to enhance early detection strategies and deepen understanding of Alzheimer’s mechanisms, paving the way for more effective treatments in the early stages of the disease.
