Administrative Supplement for 'Software Platform for Analyzing Alzheimer's and Parkinson's fMRI Connectomes'
“用于分析阿尔茨海默病和帕金森病 fMRI 连接体的软件平台”的行政补充
基本信息
- 批准号:9519378
- 负责人:
- 金额:$ 14.98万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-05-15 至 2018-08-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAdministrative SupplementAlgorithm DesignAlgorithmic SoftwareAlgorithmsAlzheimer&aposs DiseaseAreaBRAIN initiativeBiological MarkersBiomedical ResearchBiometryBrainBrain DiseasesBrain imagingBrain regionBusinessesCardiovascular DiseasesClinicClinical ResearchClinical SciencesClinical TreatmentComplexComputer softwareContractsDataData AnalysesData AnalyticsDevelopmentDiabetes MellitusDiseaseDrug TargetingElectroencephalographyEnsureExperimental DesignsFeedbackFunctional Magnetic Resonance ImagingFundingFutureGoalsGraphHumanIndustryLicensingLong-Term CareMeasuresMental HealthMethodsModelingNeurosciencesOnset of illnessOutcomeParkinson DiseasePatientsPatternPerformancePharmaceutical PreparationsPharmacologic SubstancePhasePositron-Emission TomographyPrevalencePrevention ResearchPublishingResearchResearch PersonnelScienceSmall Business Innovation Research GrantSocial WorkSoftware DesignSpeedStatistical AlgorithmStatistical MethodsSubgroupTechnologyTestingTimeTranslational ResearchUnited States National Institutes of HealthUniversitiesVisualization softwareWorkanalytical toolbiomarker discoverycloud basedcommercial applicationconnectomecostdisease diagnosisimprovedinnovationnovelnovel therapeuticsopen sourcepublic health relevancereal world applicationresearch and developmentsingle photon emission computed tomographysocialsoftware as a servicetooltranslational clinical trialtranslational neuroscienceweb based interface
项目摘要
DESCRIPTION (provided by applicant): It is estimated that the cost in the US for brain disorders per year is $500 billion for treatment and long term care, with another $400 billion in other nonmedical costs. As a consequence, reducing the burden of human brain disorders is a key focus of the NIH BRAIN Initiative, with one strategy being the use of fMRI connectomes to study brain region functioning. Current approaches for analyzing connectomes use 'off-the-shelf' statistical methods not optimized for this type of data. In this Direct to Phase II SBIR we propose
to further develop and strengthen our graphical object oriented data analysis software to solve data analysis, experimental design, and hypothesis testing problems in translational neuroscience. Product: This SBIR will produce analytical software for fMRI data in translational research. Users will access the software through a cloud-based Software-as-a-Service (SaaS) contract. The technical innovation of this SBIR statistical software designed specifically and optimized for fMRI brain imaging data is to support moving fMRI technology from basic R&D to translational clinical science. The impact of this technology are tools to improve brain imaging experimental design, improve biostatistical analysis of brain imaging data, and ultimately improve discovery of biomarkers and identify possible drug targets for clinical treatment. Long term goal: Extending our cloud-based Software-as-a-Service (SaaS) data analytics platform offers researchers an easy to use web-based interface for analyzing new and complex biomedical research data. As a platform technology, there are many applications in other areas of biomedical research that can be developed. Therefore, our business strategy is to identify the areas of science that have the greatest potential to make the move from the university research setting into the commercial arena, and that produce novel or complex data with no commercial analytics tools for translational clinical trials yet on the market. The Specific Aims of this SBIR
Direct to Phase II project are: Aim 1: Develop statistical algorithms and software. Aim 2: Validate the methods. Aim 3: Apply the methods to real data. Expected outcomes: Validated statistical software proven to be more powerful than existing methods for analyzing fMRI connectome data in translational research.
描述(申请人提供):据估计,在美国,大脑疾病每年的治疗和长期护理成本为5000亿美元,另外还有4000亿美元的其他非医疗成本。因此,减轻人类大脑疾病的负担是NIH大脑倡议的一个关键重点,其中一个策略是使用功能磁共振连接来研究大脑区域的功能。目前分析连接的方法使用的是“现成”的统计方法,不是针对这类数据进行优化的。在这个直接到第二阶段的SBIR中,我们建议
进一步开发和加强我们面向图形对象的数据分析软件,以解决翻译神经科学中的数据分析、实验设计和假设检验问题。产品:该SBIR将为翻译研究中的功能磁共振数据生产分析软件。用户将通过基于云的软件即服务(SaaS)合同访问该软件。这款专门为fMRI脑成像数据设计和优化的SBIR统计软件的技术创新之处在于,支持将fMRI技术从基础研发转移到翻译临床科学。这项技术的影响是改进脑成像实验设计、改进脑成像数据的生物统计分析,并最终改进生物标志物的发现和确定临床治疗的可能药物靶点的工具。长期目标:扩展我们基于云的软件即服务(SaaS)数据分析平台,为研究人员提供易于使用的基于Web的界面,用于分析新的复杂生物医学研究数据。作为一种平台技术,在生物医学研究的其他领域也有许多可以开发的应用。因此,我们的业务战略是确定最具潜力的科学领域,这些领域最有潜力将大学研究环境转移到商业领域,并且产生新颖或复杂的数据,而市场上还没有用于转化性临床试验的商业分析工具。这项SBIR的具体目标
第二阶段项目的目标是:目标1:开发统计算法和软件。目的2:验证方法。目的3:将这些方法应用于实际数据。预期结果:在转化性研究中,经过验证的统计软件在分析功能磁共振连接体数据方面被证明比现有方法更强大。
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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WILLIAM D. SHANNON其他文献
WILLIAM D. SHANNON的其他文献
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{{ truncateString('WILLIAM D. SHANNON', 18)}}的其他基金
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Software Platform for Analyzing Alzheimer's and Parkinson's fMRI Connectomes
用于分析阿尔茨海默病和帕金森病 fMRI 连接体的软件平台
- 批准号:
9139293 - 财政年份:2016
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8036735 - 财政年份:2010
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NEW DATA ANALYSIS METHODS FOR ACTIGRAPHY IN SLEEP MEDICINE
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8071580 - 财政年份:2009
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- 批准号:
7787041 - 财政年份:2009
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NEW DATA ANALYSIS METHODS FOR ACTIGRAPHY IN SLEEP MEDICINE
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- 批准号:
6520234 - 财政年份:2000
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