Our research project aims to improve healthcare outcomes by developing innovative methods for analyzing large datasets containing genomic, imaging, and clinical data. We want to understand how gene variations, brain structure, and health records interact to influence our risk of developing cancer and neurological conditions. By studying these relationships, we hope to predict the risk of developing a specific disease and identify new molecular targets for personalized treatments tailored to individual patients.
Our project will last for 36 months, during which we will use advanced computational approaches, including machine learning techniques, to analyze data from the UK Biobank. We will examine brain MRI scans to see how genetic variations affect brain structure and function. Then, we will explore different ways to combine information from genomics, imaging, and medical records to create more accurate predictions about disease risk.
Our research has the potential to have a significant impact on public health. Our approach will allow us to both identify people at high risk of developing diseases like cancer or Alzheimer’s disease and discover new biomarkers or druggable molecular targets that can be used for innovative early preventive interventions or personalized treatments. This could lead to better health outcomes for individuals and reduce the burden on healthcare systems. Ultimately, we aim to use cutting-edge technology to improve healthcare and help people live healthier, longer lives.
