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

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:
$15.0万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-09-15 至 2026-06-30
关键词:
AcademiaAccountingAddressAfricaAfrica South of the SaharaAfricanArtificial IntelligenceAttentionCalibrationCancer DetectionCellular PhoneCentral AfricaCervicalCervix UteriClinicalClinical DataCollaborationsCollectionComputerized Medical RecordDataData AnalysesData LinkagesData ScienceData SecurityDemocracyDermatologyDevelopmentDiabetic RetinopathyDiagnosisDiseaseEastern AfricaEcosystemEnsureEnvironmentEquipmentEye diseasesFosteringFundingFutureGeneral HospitalsGhanaGoalsGrantHealthHealth PolicyHealth PrioritiesHealth systemHealthcareImageImage AnalysisIndividualInstitutionKenyaKnowledgeLabelMachine LearningMacular degenerationMalignant neoplasm of cervix uteriManaged CareMassachusettsMedical ImagingMethodologyMethodsMissionNongovernmental OrganizationsOphthalmologistOutcomePathway interactionsPatientsPolicy MakerPolicy MakingPopulationPositioning AttributePosterior eyeball segment structureQuality ControlRadiology SpecialtyResearchResearch PersonnelResearch Project GrantsResource AllocationResourcesRoleScienceSiteSouthern AfricaSurveysTechniquesTechnologyTrainingTranslatingTrustUgandaUnited States National Institutes of HealthUniversitiesWorkalgorithm developmentartificial intelligence algorithmcare deliveryclinical careclinical databaseclinical diagnosisclinical practiceclinically relevantcollegecommunity organizationscomputerized data processingdata exchangedata harmonizationdata infrastructuredata integrationdata managementdata qualitydesignfundus imaginghealth care deliveryimplementation scienceimprovedinnovationmultidisciplinaryopen dataprogramsquality assuranceskillssymposiumtechnology diffusionuptake

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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.
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MUST Data Science Research Hub (MUDSReH)
MUST Data Science Research Hub (MUDSReH)
MUST Data Science Research Hub (MUDSReH)
Critical Care Informatics
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