MUST Data Science Research Hub (MUDSReH)

总体研究计划项目摘要。意义数据科学为撒哈拉以南地区带来巨大希望 非洲，但研究能力和适当的培训有限。医学图像尤其令人兴奋， 在这种情况下，数据科学能够促进医疗保健干部的护理服务。努力 将通过数据科学获得的知识转化为改善的临床护理， 执行科学。战略性多学科、多机构伙伴关系将是 数据科学对非洲解决方案的发展和最终影响。创新这项建议是 创新之处在于：1）将数据科学与医学图像结合使用，以推进临床护理; 2）整合 数据科学与实施科学，以促进临床影响。Approach.姆巴拉拉大学数据 乌干达的科学研究中心（MUDSReH）将使用多种技术来提高对 医学图像，并采用机器学习和人工智能等关键数据科学方法， 扩大其在撒哈拉以南非洲的使用。将通过实施加强临床影响 科学方法将为数据科学和实施科学提供正式培训， 将通过区域首脑会议和协作，促进不断扩大的努力。两个初始 研究项目-优化后眼底成像诊断后段眼病和移动的- 基于手机的宫颈图像来检测癌症-将涉及与眼科医师学院的合作伙伴关系 肯尼亚东部、中部和南部非洲发展问题国际会议和夸梅·恩克鲁玛科学大学， 加纳的技术。马萨诸塞州理工学院将为 数据管理和分析，以及马萨诸塞州总医院将支持使用实施 科学和其他相关内容领域的个人研究项目。每个项目都将与当地 卫生部、社区组织和/或技术合作伙伴，以推进以下使命： 利用医学图像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， 组织推动医学成像的数据科学。所有合作伙伴都将为共同的 数据处理和分析的基础设施。我们将建立行政和技术 数据交换机制，考虑到必要的数据安全以及质量保证和控制。 我们将进一步创造途径，以方便扩展，包括更多的研究项目， 医学成像（例如，放射学和皮肤病学）在多个非洲机构。 2.将实施科学与数据科学相结合，以提高临床影响。所有研究 MUDSReH中的项目将包括实施科学方法，以确保开发的 技术以符合当地需要和优先事项的实际方式到达最终用户手中。

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.