Machine Learning and Large-scale Imaging analytics for dimensional representations of brain trajectories in aging and preclinical Alzheimer's Disease: The brain aging chart and the iSTAGING consortium

摘要 家长基金一直在建立一个真正独特的数据库，其中包括来自 65,000个个体和16个不同的研究。它一直在构建机器学习模型和 旨在捕捉脑老化异质性并推导认知预测模型的生物标记物 拒绝。目前的补充资料将为使这些管道非常容易获得奠定基础 通过云计算。更具体地说，这一补充的重点将是建设基础设施 对于在AWS云中运行的基于Web的门户，这将允许无缝地拖放核磁共振 用于父程序开发的管道的应用。这将有助于更广泛地访问 这些管道无需设置本地软件并熟悉复杂的 核磁共振数据集和机器学习管道。

Abstract The parent grant has been building a truly unique database of MRI, clinical and cognitive data from over 65,000 individuals and 16 distinct studies. It has been constructing machine learning models and biomarkers aiming to capture the heterogeneity of brain aging and derive predictive models of cognitive decline. The current supplement will build the foundation for making these pipelines available very easily through cloud computing. More specifically, the focus of this supplement will be to build the infrastructure for a web-based portal running n the AWS cloud, which will allow for seamless “drag-and-drop” of MRIs for application of the pipelines developed by the parent program. This will facilitate the wide access of these pipelines without the need to set up local software and familiarize with complex preprocessing of MRI datasets and machine learning pipelines.