Department of Genetics, Stanford University, Stanford, CA, USA.
Stanford Center for Genomics and Personalized Medicine, Stanford University, Stanford, CA, USA.
Nat Commun. 2021 Oct 1;12(1):5757. doi: 10.1038/s41467-021-26040-1.
The large amount of biomedical data derived from wearable sensors, electronic health records, and molecular profiling (e.g., genomics data) is rapidly transforming our healthcare systems. The increasing scale and scope of biomedical data not only is generating enormous opportunities for improving health outcomes but also raises new challenges ranging from data acquisition and storage to data analysis and utilization. To meet these challenges, we developed the Personal Health Dashboard (PHD), which utilizes state-of-the-art security and scalability technologies to provide an end-to-end solution for big biomedical data analytics. The PHD platform is an open-source software framework that can be easily configured and deployed to any big data health project to store, organize, and process complex biomedical data sets, support real-time data analysis at both the individual level and the cohort level, and ensure participant privacy at every step. In addition to presenting the system, we illustrate the use of the PHD framework for large-scale applications in emerging multi-omics disease studies, such as collecting and visualization of diverse data types (wearable, clinical, omics) at a personal level, investigation of insulin resistance, and an infrastructure for the detection of presymptomatic COVID-19.
从可穿戴传感器、电子健康记录和分子分析（例如基因组学数据）中获得的大量生物医学数据正在迅速改变我们的医疗保健系统。生物医学数据规模和范围的不断扩大不仅为改善健康结果带来了巨大的机会，还带来了从数据采集和存储到数据分析和利用的新挑战。为了应对这些挑战，我们开发了个人健康仪表板（PHD），该仪表板利用最先进的安全和可扩展技术，为生物医学大数据分析提供端到端的解决方案。PHD 平台是一个开源软件框架，可以轻松配置和部署到任何大数据健康项目中，用于存储、组织和处理复杂的生物医学数据集，支持在个体和队列层面进行实时数据分析，并确保参与者在每个步骤的隐私。除了介绍系统外，我们还说明了 PHD 框架在新兴的多组学疾病研究中的大规模应用，例如个人层面的多样化数据类型（可穿戴、临床、组学）的收集和可视化、胰岛素抵抗的研究以及无症状 COVID-19 的检测基础设施。
