Integrating Personalized Brain Simulation, Machine Learning, and Multimodal Neuroimaging for Early Detection of Alzheimer's Disease: A New Data-Driven Methodological Framework

整合个性化大脑模拟、机器学习和多模态神经影像以早期检测阿尔茨海默病：一种新的数据驱动方法框架

• 批准号: 412543
• 负责人: Dhindsa Jaskiret
• 金额: $ 10.93万
• 依托单位: Charit - Universitätsmedizin Berlin (Germany)
• 依托单位国家: 加拿大
• 项目类别: Fellowship Programs
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-10-01 至 2022-10-01
• 项目状态: 已结题
• 来源: https://webapps.cihr-irsc.gc.ca/decisions/p/project_details.html?applId=412543&lang=en
• 关键词: Artificial Intelligence; Brain Simulation; Data Science; Machine Learning; Multimodal Modelling; Neurodegeneration; Neuroimaging; Personalized Medicine; Precision Medicine; Topological Data Analysis

Maintaining a healthy brain through one's lifespan depends on the complex interaction between the brain, genetics, and lifestyle. With a rapidly aging population, the prevalence of neurodegenerative diseases like Alzheimer's Disease are significantly incr

在人的一生中保持大脑健康取决于大脑、遗传和生活方式之间复杂的相互作用。随着人口迅速老龄化，阿尔茨海默病等神经退行性疾病的患病率显着增加