Administrative Supplement to 1U54EB020404 award Mobile Data to Knowledge: Combining Genomic and Mobile Data Around Physical Activity

1U54EB020404 奖移动数据到知识的行政补充：围绕身体活动结合基因组和移动数据

• 批准号: 9198625
• 负责人: Santosh Kumar
• 金额: $ 5.03万
• 依托单位: UNIVERSITY OF MEMPHIS
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-29 至 2018-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9198625
• 关键词: Address; Administrative Supplement; Algorithms; Architecture; Area; Asthma; Award; Back; Behavior; Behavioral; Big Data; Biological; Biomedical Research; Cardiovascular Diseases; Chronic Disease; Clinical; Communities; Complex; Computer software; Computing Methodologies; Congestive Heart Failure; Data; Data Analyses; Data Analytics; Data Science; Devices; Diabetes Mellitus; Disease; Documentation; E-learning; Educational Curriculum; Environment; Environmental Risk Factor; Etiology; Event; Foundations; Funding; Genetic; Genomics; Goals; Health; Healthcare; Image; Imagery; Individual; Intervention; Investments; Knowledge; Knowledge Discovery; Malignant Neoplasms; Measures; Medicine; Mental Depression; Methods; Mining; Obesity; Participant; Patient Care; Patient Monitoring; Patient Self-Report; Patients; Pattern; Persons; Physical activity; Population; Prevention strategy; Preventive; Process; Provider; Relapse; Research Personnel; Research Training; Risk Factors; Science; Semantics; Series; Smoker; Software Tools; Staging; Standardization; Structure; System; Technology; Time; Training; United States; United States National Institutes of Health; Vision; base; big biomedical data; burden of illness; care delivery; computer infrastructure; data to knowledge; design; disorder risk; experience; handheld mobile device; improved; instructor; mHealth; open source; prevent; sensor; social; software development; theories; tool; treatment response; usability

DESCRIPTION (provided by applicant): Rapid advances in technology, are leading to field-deployable mobile sensing devices that can now be used to quantify complex dynamics across time of key physical, biological, behavioral, social, and environmental factors that contribute to health and disease risk. These data will enable us to break through to the next level of biomedical understanding of causation in complex disorders. While ongoing efforts have made significant strides in the analysis of "big data" in the areas of genomics, imaging, and EHR, significant new investment is needed to develop and disseminate data analytics tools specific to the unique features of mobile sensor data (e.g., high volume, velocity, variety, variability, and versatility) to convert this wealth of data into information, knowledge, and action. Investment in strong, open, scientific, and computational infrastructure for mobile "big data" at this early stag promises outsize returns to advance science and improve health. The Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K) will generate generalizable theory, methods, tools, and software, to address major barriers to processing complex mobile sensor data and its use in biomedical knowledge discovery and just-in-time care delivery, laying the foundation for P5 Medicine. It will develop and implement a standards-based, interoperable, extensible and open-source big data software platform for efficient implementation of MD2K data analytics. The MD2K Center will demonstrate the feasibility, utility, and generalizability of the MD2K approach by implementing the entire MD2K data analytics system in the context of two biomedical applications - reducing relapse among abstinent daily smokers and reducing readmission among congestive heart failure (CHF) patients. All the tools and software developed by the Center will be freely available as standards-compliant and open-source with documentation to engage data science researchers in advancing the science of MD2K and its integration with other biomedical big data such as EHRs, genomics, and imaging. The Center will provide training materials to help biomedical researchers install the MD2K software on their mobile devices and servers to collect mobile sensor data and analyze these data for biomedical discovery.

描述（由申请人提供）：技术的快速进步导致了可现场部署的移动的传感设备，其现在可以用于量化关键物理、生物、行为、社会和环境因素的跨时间的复杂动态，这些因素有助于 健康和疾病风险。这些数据将使我们能够突破对复杂疾病因果关系的生物医学理解的新水平。虽然正在进行的努力在基因组学、成像和EHR领域的“大数据”分析方面取得了重大进展，但需要大量新的投资来开发和传播特定于移动的传感器数据的独特特征的数据分析工具（例如，高容量、速度、多样性、可变性和多功能性）将这些丰富的数据转换为信息、知识和行动。在这个早期阶段，为移动的“大数据”投资强大、开放、科学和计算基础设施，有望为推进科学和改善健康带来巨大回报。 移动的传感器数据到知识（MD 2K）卓越中心将产生可推广的理论、方法、工具和软件，以解决处理复杂移动的传感器数据及其在生物医学知识发现和及时护理提供中的应用的主要障碍，为P5医学奠定基础。它将开发和实施一个基于标准、可互操作、可扩展和开源的大数据软件平台，以有效实施MD 2K数据分析。MD 2K中心将通过在两个生物医学应用的背景下实施整个MD 2K数据分析系统来证明MD 2K方法的可行性、实用性和普遍性-减少每日戒烟吸烟者的复发和减少充血性心力衰竭（CHF）患者的再入院。该中心开发的所有工具和软件都将作为标准兼容和开源的文档免费提供，以吸引数据科学研究人员参与推进MD 2K科学及其与其他生物医学大数据（如EHR，基因组学和成像）的整合。该中心将提供培训材料，帮助生物医学研究人员在他们的移动的设备和服务器上安装MD 2K软件，以收集移动的传感器数据，并分析这些数据用于生物医学发现。