Data Management and Statistical Core
数据管理与统计核心
基本信息
- 批准号:10369036
- 负责人:
- 金额:$ 44.74万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-07-01 至 2025-02-28
- 项目状态:未结题
- 来源:
- 关键词:Aged, 80 and overAlzheimer&aposs DiseaseAlzheimer&aposs Disease Core CenterAreaAwardBiological MarkersBiomedical EngineeringBiometryClinicalCommunitiesComputer softwareConsensusConsultConsultationsCustomDataData FilesDatabase Management SystemsDatabasesDementiaDetectionDiagnosisEarly DiagnosisEducationEnsureFosteringGenerationsGoalsGrantHealth Insurance Portability and Accountability ActHomeInformation DistributionInstitutional Review BoardsInternationalInternetIntranetInvestigationKnowledgeLeadershipMediatingMedical InformaticsNewsletterOregonPlayProceduresResearchResearch PersonnelResearch Project GrantsRoleSamplingScienceSecureSourceSpecific qualifier valueStatistical Data InterpretationStatistical ModelsStructureTechnologyTimeTrainingaging brainauthoritycollaborative environmentdata integritydata managementdata sharingdementia riskdesigndigitaleffective therapyenvironmental enrichment for laboratory animalsinnovationmeetingsmild cognitive impairmentneuroimagingneuropathologynoveloutreachpreventprogramsrecruitrepositoryresponsesensorsuccess
项目摘要
Project Summary: Data Management and Statistical Core!
The Data Management and Statistical Core (DMSC) is aligned to support the overall goal of the Oregon
ADRC’s two overarching aims: (1) to focus on early detection of change in order to define mechanisms
supporting healthy brain aging and the transition to MCI and early dementia, and (2) to facilitate developing
effective therapies to prevent or mediate these transitions.
Fostering research directed toward the pre-symptomatic to early MCI spectrum, risk factors of dementia among
the oldest old and novel treatments, the OADC’s DMSC supports an array of distinct investigations ranging
from statistical modeling of longitudinal biomarker data to real-time change detection through automated in-
home activity sensor assessments. These activities advance OADRC research goals directed toward
innovation and discovery in the areas of the pre-symptomatic to early Mild Cognitive Impairment (MCI)
spectrum, risk factors of dementia among the oldest old and novel treatments. This research is optimally
conducted as team science across multiple units, centers and departments including the biomedical
engineering and medical informatics departments. In this exceptionally collaborative and interactive
environment, the OADRC DMSC is required more than ever to ensure the integrity of the data coming from
multiple sources and to provide prompt distribution of customized data files as well as statistically thoughtful
and appropriate analyses and consultations for a wide range of researchers. Within this context and in
response to the RFA, the DMSC’s Specific Aims are to:
1. Develop and maintain a functional longitudinal research database and share the data
2. Collaborate with the National Alzheimer’s Coordinating Center (NACC) and related centers
3. Provide biostatistical analyses and consultation
4. Provide an enriched environment that increases statistical knowledge for early-stage investigators,
trainees and OADC affiliates.
项目概要:数据管理与统计核心!
数据管理和统计核心 (DMSC) 旨在支持俄勒冈州的总体目标
ADRC 的两个总体目标:(1) 注重早期发现变化以定义机制
支持健康的大脑老化以及向 MCI 和早期痴呆的过渡,以及 (2) 促进发展
预防或介导这些转变的有效疗法。
促进针对症状前到早期 MCI 谱系、痴呆症危险因素的研究
作为最古老和新颖的治疗方法,OADC 的 DMSC 支持一系列不同的研究,包括
从纵向生物标志物数据的统计建模到通过自动化的实时变化检测
家庭活动传感器评估。这些活动推进了 OADRC 的研究目标
症状前到早期轻度认知障碍 (MCI) 领域的创新和发现
最古老和新颖的治疗方法中痴呆症的谱系、危险因素。本研究最优化
作为跨多个单位、中心和部门(包括生物医学部门)的团队科学进行
工程和医学信息学系。在这个异常协作和互动的环境中
环境中,OADRC DMSC 比以往任何时候都更需要确保来自以下位置的数据的完整性
多个来源并提供定制数据文件的及时分发以及统计考虑
以及为广大研究人员提供适当的分析和咨询。在此背景下并在
作为对 RFA 的回应,DMSC 的具体目标是:
1. 开发和维护功能性纵向研究数据库并共享数据
2. 与国家阿尔茨海默病协调中心(NACC)及相关中心合作
3. 提供生物统计分析和咨询
4. 提供丰富的环境,为早期研究人员增加统计知识,
学员和 OADC 附属机构。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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HIROKO Hayama DODGE其他文献
HIROKO Hayama DODGE的其他文献
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{{ truncateString('HIROKO Hayama DODGE', 18)}}的其他基金
Identification of Mild Cognitive Impairment using Machine Learning from Language and Behavior Markers
使用机器学习从语言和行为标记识别轻度认知障碍
- 批准号:
10709094 - 财政年份:2021
- 资助金额:
$ 44.74万 - 项目类别:
Identification of Mild Cognitive Impairment using Machine Learning from Language and Behavior Markers
使用机器学习从语言和行为标记识别轻度认知障碍
- 批准号:
10212669 - 财政年份:2021
- 资助金额:
$ 44.74万 - 项目类别:
Web-enabled social interaction to delay cognitive decline among seniors with MCI: Phase I
基于网络的社交互动可延缓 MCI 老年人认知能力下降:第一阶段
- 批准号:
9311584 - 财政年份:2017
- 资助金额:
$ 44.74万 - 项目类别:
Web-enabled social interaction to delay cognitive decline among seniors with MCI: Phase I
基于网络的社交互动可延缓 MCI 老年人认知能力下降:第一阶段
- 批准号:
9898209 - 财政年份:2017
- 资助金额:
$ 44.74万 - 项目类别:
Web-enabled social interaction to delay cognitive decline among seniors with MCI: Phase I Administrative Supplement
基于网络的社交互动可延缓 MCI 老年人认知能力下降:第一阶段行政补充
- 批准号:
10363310 - 财政年份:2017
- 资助金额:
$ 44.74万 - 项目类别:
Web-enabled social interaction to delay cognitive decline among seniors with MCI: Phase I
基于网络的社交互动可延缓 MCI 老年人认知能力下降:第一阶段
- 批准号:
9930344 - 财政年份:2017
- 资助金额:
$ 44.74万 - 项目类别:
Conversational Engagement as a Means to Delay Onset AD: Phase II Administrative Supplement
对话参与作为延迟 AD 发作的一种手段:第二阶段行政补充
- 批准号:
10058784 - 财政年份:2016
- 资助金额:
$ 44.74万 - 项目类别:
Web-enabled social interaction to delay cognitive decline among seniors with MCI: Phase I
基于网络的社交互动可延缓 MCI 老年人认知能力下降:第一阶段
- 批准号:
9348726 - 财政年份:2016
- 资助金额:
$ 44.74万 - 项目类别: