The Advanced Analytics Research Core will support all four Research Projects at the University of Rochester Udall Center

摘要 UR-Udall中心的高级分析研究核心将联合深厚的生物统计学专业知识和PD 在罗切斯特大学与来自 罗切斯特大学、约翰·霍普金斯大学、阿斯顿大学、赛奇生物网络公司和麻省理工学院支持UR-Udall 中心的研究项目，并进行新颖的跨项目分析。这些项目将依赖于大数据 集合，包括最大的PD临床试验数据存储库(项目1)和来自 智能手机(项目3)和新型主要无源传感器(项目4)。高级分析研究 CORE将依赖于CORE调查人员的人才、各个机构的资源和数据 卫生技术中心的管理专门知识开展其工作。 为了启用跨项目分析，我们将招募一组将 在两年内接受标准化的住院评估，此外至少要进行 属于研究项目3和4的四个传感器中的三个，特别是智能手机、可穿戴传感器、 基于视频的传感器和基于无线电波的传感器。该小组将是第一批将传统临床与 在临床和现实环境中，通过多个新型传感器的评估进行PD评估。如此之高 特征化的小组将能够评估传感器的相对能力，以区分那些患有PD的人和 那些没有，以检测疾病的进展，评估对当前药物的反应，并产生新的 对帕金森病的洞察，目前还不能从临床测量中确定。 除了UR-Udall中心的工作外，高级分析研究核心将是 Udall中心网络，还将吸引、培养和指导生物统计和计算科学人才 为了更大的警局社区。

SUMMARY The Advanced Analytics Research Core of the UR-Udall Center will unite deep biostatistical expertise and PD research experience at the University of Rochester with leading computational science talent from the University of Rochester, Johns Hopkins, Aston University, Sage Bionetworks, and MIT to support the UR-Udall Center's research projects and to conduct novel cross-project analyses. These projects will rely on large data sets, including the largest repository of PD clinical trial data (Project 1) and enormous data streams from smartphones (Project 3) and novel principally passive sensors (Project 4). The Advanced Analytics Research Core will rely on the talents of the Core's investigators, the resources of the individual institutions, and the data management expertise of the Center for Health + Technology to conduct its work. To enable cross-project analyses, we will enroll a group of “Super Users” (50 with PD and 20 without) that will undergo a standardized battery of in-clinic assessments over two years in addition to evaluation by at least three of the four sensors that are part of Research Projects 3 and 4, specifically smartphone, wearable sensor, video-based sensor, and radio wave-based sensor. This group will be one of the first to pair traditional clinical PD assessments with evaluations by multiple novel sensors in clinical and real-world settings. This highly characterized group will enable evaluation of the sensors' relative ability to differentiate those with PD from those without, to detect disease progression, to assess response to current medications, and to produce novel insights into PD that cannot be ascertained currently from in-clinic measurements. Beyond the work of the UR-Udall Center, the Advanced Analytics Research Core will be a resource for the Udall Center network and will also attract, develop, and mentor biostatistical and computational science talent for the greater PD community.