ScHARe (Science Collaborative for Health disparities and Artificial intelligence bias Reduction) Cloud Research Collaboration Platform
ScHARe (Science Collaborative for Health disparities and Artificial intelligence bias Reduction) Cloud Research Collaboration Platform
批准号:
10723720
负责人:
DIANE MICHAULT
金额:
$40.0万
依托单位:
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依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-04-22 至 2023-04-21
关键词:
Artificial IntelligenceBig DataCollaborationsConsensusDataData ElementData Science CoreDevelopmentHealth PolicyHealth SciencesResearchResearch PersonnelResourcesRoleScienceSocial SciencesTrainingUnited States National Institutes of Healthdata sharinghealth care deliveryhealth disparityinteroperabilityoutreachrepositorytool
中文摘要
ScHARe将填补NIH数据库中的空白,专注于社会科学数据(SDoH),将成为用户开发偏见缓解工具的平台,并履行NIH数据共享政策,用于健康差异(HD),SDoH和医疗保健提供调查员/受资助者和内部调查员。需要知识渊博、技能熟练的云开发人员和数据管理员来加快ScHARe资源的完成和启动。此外,HD和SDoH核心数据元素可以提高互操作性,并对新的代表性不足的用户进行培训,这对于增加多样化的人工智能劳动力和促进大数据的使用以进一步了解健康差异,特别是SDoH的作用至关重要。
英文摘要
ScHARe will fill a gap in NIH repositories focusing on social science data (SDoH), is will be a platform for the development of bias mitigation tools by users, and fulfill NIH Data Sharing policy for health disparity (HD), SDoH and healthcare delivery investigators/grantees and intramural investigators. Knowledgeable skilled cloud developers and data curators are needed to expedite the completion and launch of the ScHARe resource. In addition, HD and SDoH core data elements to increase interoperability and training of new underrepresented users are critical to increasing a diverse AI workforce and promote the use of big data to further understand Health Disparities, especially the role of SDoH.
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会议论文
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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批准号:--
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项目类别:合作创新研究团队
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资助金额:--
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批准年份:2024
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负责人:姚韬
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依托单位: