An international research team led by the Hong Kong University of Science and Technology (HKUST) has developed an artificial intelligence (AI)-based model that uses genetic information to predict an individual’s risk of developing Alzheimer’s disease (AD) well before symptoms occur. This study paves the way for using deep learning methods to predict the risks of diseases and uncover their molecular mechanisms, which could revolutionize the diagnosis, interventions, and clinical research on AD and other common diseases such as cardiovascular diseases. The team established one of the first deep learning models for estimating AD polygenic risks in both European-descent and Chinese populations, which more accurately classify patients with AD and stratify individuals into distinct groups based on disease risks associated with alterations of various biological processes. By combining the new deep learning model with genetic testing, an individual’s lifetime risk of developing AD can be estimated with more than 70% accuracy.
Related Posts
