The Hong Kong University of Science and Technology said on the 7th that an international research team led by the university has recently developed a set of artificial intelligence models to use genetic information to make early risk prediction for Alzheimer's disease. A team led by Ye Yuru, President of HKUST, and Chen Lei, Director of HKUST Data Institute, established an in-depth learning model to assess the polygenic risk of Alzheimer's disease in European and Chinese populations. This study combines the new deep learning model with Genetic testing, which can assess the risk of Alzheimer's disease in an individual's life, with an accuracy rate of more than 70%. According to Hong Kong University of Science and Technology, Alzheimer's disease is a Genetic disorder, which can be attributed to genetic variation. Due to the fact that Alzheimer's disease is caused by multiple risk gene loci, testing one risk gene alone may not be sufficient to identify high-risk individuals. Therefore, the development of a test that integrates multiple risk gene information of Alzheimer's disease is crucial to accurately assess the Relative risk of individuals suffering from Alzheimer's disease in their lifetime. Ye Yuru stated that their research demonstrates the effectiveness of deep learning methods in genetic research and Alzheimer's disease risk prediction. This will accelerate the large-scale risk screening and risk grading of Alzheimer's disease, providing new research ideas for the pathogenesis and worsening mechanism of the disease. Chen Lei stated that this study demonstrates the benefits of applying artificial intelligence in biological sciences for biomedical and disease related research. The research was carried out jointly by HKUST, researchers from the Chinese Academy of Sciences Shenzhen Institute of Advanced Technology, University College London and doctors from two public hospitals in Hong Kong. The relevant research results have recently been published in Medical Newsletter. (New News Agency)