MUST Data Science Research Hub (MUDSReH) - Democratized Trusted Research Environment (dTRE)

MUST 数据科学研究中心 (MUDSReH) - 民主化可信研究环境 (dTRE)

基本信息

批准号：
10826921
负责人：
Leo Anthony G Celi
金额：
$ 15万
依托单位：
MBARARA UNIVERSITY/SCIENCE/ TECHNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-15 至 2026-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10826921
关键词：
Academia Accounting Address Africa Africa South of the Sahara African Artificial Intelligence Attention Calibration Cancer Detection Cellular Phone Central Africa Cervical Cervix Uteri Clinical Clinical Data Collaborations Collection Computerized Medical Record Data Data Analyses Data Linkages Data Science Data Security Democracy Dermatology Development Diabetic Retinopathy Diagnosis Disease Eastern Africa Ecosystem Ensure Environment Equipment Eye diseases Fostering Funding Future General Hospitals Ghana Goals Grant Health Health Policy Health Priorities Health system Healthcare Image Image Analysis Individual Institution Kenya Knowledge Label Machine Learning Macular degeneration Malignant neoplasm of cervix uteri Managed Care Massachusetts Medical Imaging Methodology Methods Mission Nongovernmental Organizations Ophthalmologist Outcome Pathway interactions Patients Policy Maker Policy Making Population Positioning Attribute Posterior eyeball segment structure Quality Control Radiology Specialty Research Research Personnel Research Project Grants Resource Allocation Resources Role Science Site Southern Africa Surveys Techniques Technology Training Translating Trust Uganda United States National Institutes of Health Universities Work algorithm development artificial intelligence algorithm care delivery clinical care clinical database clinical diagnosis clinical practice clinically relevant college community organizations computerized data processing data exchange data harmonization data infrastructure data integration data management data quality design fundus imaging health care delivery implementation science improved innovation multidisciplinary open data programs quality assurance skills symposium technology diffusion uptake

项目摘要

Overall Research Plan Project Summary. Significance. Data science hold great promise for sub-Saharan Africa, yet research capacity and appropriate training are limited. Medical images are particularly exciting for data science in this setting given their ability to facilitate care delivery across healthcare cadres. Efforts to translate the knowledge gained through data science into improved clinical care can be fostered through implementation science. Strategic multi-disciplinary, multi-institutional partnerships will be key for the development and ultimate impact of data science for African-based solutions. Innovation. This proposal is innovative in 1) its use of data science with medical images for advancing clinical care, and 2) integration of data science with implementation science to promote clinical impact. Approach. The Mbarara University Data Science Research Hub (MUDSReH) in Uganda will use multiple technologies to improve the capture of medical images and employ key data science methods, such as machine learning and artificial intelligence, to expand their utilization in sub-Saharan Africa. Clinical impact will be strengthened through implementation science methods. Formal training will be available for both data science and implementation science, and ongoing expansion of efforts will be promoted through regional summits and collaboration. The two initial research projects—optimized posterior fundus imaging to diagnose posterior segment eye disease and mobile- phone based cervical images to detect cancer—will involve partnerships with the College of Ophthalmologists of Eastern, Central and Southern Africa in Kenya and the Kwame Nkrumah University of Science and Technology in Ghana, respectively. Massachusetts Institute of Technology will provide technical support for data management and analysis, and Massachusetts General Hospital will support the use of implementation science and other relevant content areas for individual research projects. Each project will work with local Ministries of Health, community-based organizations, and/or technology partners to advance the mission of harnessing medical images for improved clinical outcomes and impact. Our specific aims are as follows: 1. To integrate all partnering academic institutions, technology companies, and non-governmental organizations to advance data science for medical imaging. All partners will contribute to a common infrastructure for data processing and analysis. We will establish both the administrative and technical mechanisms for data exchange, accounting for necessary data security and quality assurance and control. We will further create pathways for facile expansion to include additional research projects involving medical imaging (e.g., in radiology and dermatology) at multiple African institutions. 2. To integrate implementation science with data science to advance clinical impact. All research projects in the MUDSReH will include implementation science methodologies to ensure the developed technology reaches the end user in practical ways that meet local needs and priorities.

总体研究计划项目概要。数据科学对撒哈拉以南地区有着巨大的前景。非洲，但研究能力和适当的培训是有限的，医学图像尤其令人兴奋。数据科学在这种情况下有能力促进医疗保健干部的护理服务。将通过数据科学获得的知识转化为改进的临床护理可以通过战略性的多学科、多机构伙伴关系将是关键。数据科学对非洲创新的发展和最终影响。创新之处在于 1) 将数据科学与医学图像结合使用来推进临床护理，以及 2) 整合姆巴拉拉大学数据方法的数据科学实施与科学促进临床影响。乌干达科学研究中心 (MUDSReH) 将使用多种技术来提高捕获医学图像并采用关键的数据科学方法，例如机器学习和人工智能，通过实施将加强其在撒哈拉以南非洲的利用。科学方法将提供数据科学和实施科学的正式培训，以及将通过区域首脑会议和合作推动不断扩大努力。研究项目——优化后眼底成像以诊断眼后段疾病和移动- 基于手机的宫颈图像检测癌症——将涉及与眼科医师学院的合作肯尼亚东部、中部和南部非洲和夸梅·恩克鲁玛科技大学加纳理工学院将分别提供技术支持。数据管理和分析，麻省总医院将支持使用实施每个项目都将与当地的科学和其他相关内容领域合作。卫生部、社区组织和/或技术合作伙伴推进以下使命：利用医学图像来改善临床结果和影响。我们的具体目标如下： 1. 整合所有合作的学术机构、科技公司和非政府组织推动医学成像数据科学的组织所有合作伙伴都将为共同的目标做出贡献。我们将建立数据处理和分析的基础设施。数据交换机制，考虑必要的数据安全以及质量保证和控制。我们将进一步创造便利扩展的途径，以包括涉及以下领域的其他研究项目：多个非洲机构的医学成像（例如放射学和皮肤科）。 2. 将科学实施与数据科学相结合，以促进所有研究的临床影响。 MUDSReH 中的项目将包括实施科学方法，以确保开发技术以满足当地需求和优先事项的实用方式到达最终用户。