Risk prediction: Our research team is establishing artificial intelligence (AI) models that utilize genetic information to predict the risk of Alzheimer’s disease. This approach can also stratify individuals into low, medium, and high-risk groups based on their relative risk of developing Alzheimer’s disease. Early detection and monitoring: The team has developed a simple, accurate, and non-invasive blood test for the early screening, staging, and monitoring of Alzheimer’s disease. By leveraging cutting-edge proteomic technology and self-developed mathematic algorithms, this test can measure changes in blood protein biomarkers and accurately distinguish patients with Alzheimer’s disease (accuracy >96%) or mild cognitive impairment (accuracy >87%) from cognitively normal people. It can also evaluate the health status of various body systems in individuals. This test can greatly facilitate early and improved management of Alzheimer’s, including early detection to assist in clinical diagnosis, screening suitable individuals for clinical trials and drug treatment, evaluating drug efficacy and response, and monitoring disease progression.