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)

• 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
• 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

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.

总体研究计划项目总结。的意义。数据科学为撒哈拉以南地区带来了巨大的希望