mDOT TR&D1 (Discovery) - Enabling the Discovery of Temporally-Precise Intervention Targets and Timing Triggers from mHealth Biomarkers via Uncertainty-Aware Modeling of Personalized Risk Dynamics

项目负责人：Bogg，Jim主要研究者：Kumar，Santosh TR&D1：能够发现时间精确的干预目标和时间触发器， 通过个性化风险动态的不确定性感知建模的mHealth生物标志物 负责人：Jim Bogg博士，格鲁吉亚理工学院; 10%努力（0.9 CM） 翻译后摘要：mHealth中心的发现，优化和翻译的时间精确干预 (the mDOT中心）将使一个新的模式，时间精确的医学，以保持健康和管理 慢性病日益加重的负担。mDOT中心将开发和传播方法，工具， 和基础设施所需的研究人员追求的发现，优化和翻译的时间- 精准的移动健康干预措施。这种干预，当动态个性化的时刻到时刻， 每个人的生物心理社会环境背景，将促成一个急需的转变， 通过使患者能够启动和维持健康的生活方式的选择， 管理，治疗，在某些情况下甚至防止医疗条件的发展。有组织 围绕三个技术研究与开发（TR&D）项目，mDOT代表了一个独特的国家 资源，将开发多种技术创新，并支持其转化为研究和 移动健康社区以易于部署的可穿戴设备、可穿戴设备应用程序和 智能手机，以及配套的mHealth云系统，全部开源。 TR&D1将开发、评估和传播分析人口规模多模态时间序列的方法， 移动健康生物标志物，以使研究能够识别瞬间的风险因素和风险动态， 这些数据来源中存在不确定性和缺失。 TR&D1将在三个目标下实现这一目标。目标1将解决mHealth领域研究中缺失的传感器数据，并开发 使用新型深度概率神经网络的最先进的插补模型， 生物标志物计算图的性质。目标2将解决压缩生物标志物的集合， 作为特定不良健康事件的风险因素纳入单一风险评分，以支持在线调整 TR&D2中的决策规则，使用包括多个不良事件及其 contexts.除了风险评分，我们还将开发干预和参与者接受性模型 参与，这补充了指导干预措施设计的风险评估。目标3将开始处理 关键问题是提供基于模型的工具，以确定哪些潜在风险因素实际上影响风险， 为不同的人提供不同的背景，以支持干预设计过程。TR&D1将发挥作用 与合作项目，以确保它专注于面临的最紧迫的问题，移动的健康 研究社区。TR&D1将以软件形式向服务项目和社区传播其技术 软件包和基于云的数据分析工具，以确保这些技术的可用性， 是交通部调查组的外部人员TR&D1将与其他TR&D合作， 项目，培训和传播核心，以及行政核心，以最大限度地提高研究和 TR&D1技术的社会影响。 1

Project Lead: Rehg, Jim Primary Investigator: Kumar, Santosh TR&D1: Enabling the Discovery of Temporally-Precise Intervention Targets and Timing Triggers from mHealth Biomarkers via Uncertainty-Aware Modeling of Personalized Risk Dynamics Lead: Dr. Jim Rehg, Georgia Tech; 10% effort (0.9 CM) Abstract: The mHealth Center for Discovery, Optimization & Translation of Temporally-Precise Interventions (the mDOT Center) will enable a new paradigm of temporally-precise medicine to maintain health and manage the growing burden of chronic diseases. The mDOT Center will develop and disseminate the methods, tools, and infrastructure necessary for researchers to pursue the discovery, optimization and translation of temporally- precise mHealth interventions. Such interventions, when dynamically personalized to the moment-to-moment biopsychosocial-environmental context of each individual, will precipitate a much-needed transformation in healthcare by enabling patients to initiate and sustain the healthy lifestyle choices necessary for directly managing, treating, and in some cases even preventing the development of medical conditions. Organized around three Technology Research & Development (TR&D) projects, mDOT represents a unique national resource that will develop multiple technological innovations and support their translation into research and practice by the mHealth community in the form of easily deployable wearables, apps for wearables and smartphones, and a companion mHealth cloud system, all open-source. TR&D1 will develop, evaluate and disseminate methods to analyze population-scale multi-modal time series of mHealth biomarkers to enable research on identifying the momentary risk factors and risk dynamics that drive adverse health outcomes, while accounting for the uncertainty and missingness inherent in these data sources. TR&D1 will do this under three aims. Aim 1 will address missing sensor data in mHealth field studies and develop state-of-the art imputation models using novel deep probabilistic neural networks that leverage the hierarchical nature of biomarker computation graphs. Aim 2 will address compressing a collection of biomarkers that serve as risk factors for a particular adverse health event into a single risk score, to support the online adaptation of decision rules in TR&D2, using longitudinal data that include multiple instances of adverse events and their contexts. In addition to risk scoring, we will also develop models for receptivity to intervention and participant engagement, which complement the assessment of risk in guiding intervention design. Aim 3 will begin to tackle the critical issue of providing model-based tools for identifying which potential risk factors actually impact risk in different contexts for different individuals, in order to support the intervention design process. TR&D1 will work with its collaborative projects to ensure that it focuses on the most pressing problems facing the mobile health research community. TR&D1 will disseminate its technologies to service projects and the community as software packages and cloud-based data analysis tools, to ensure the usability of these technologies by investigators who are external to the mDOT investigating team. TR&D1 will synergistically work in partnership with the other TR&D projects, the Training and Dissemination Core, and the Administration Core to maximize both the research and societal impact of TR&D1 technologies. 1