UZIMA-DS: UtiliZing health Information for Meaningful impact in East Africa through Data Science
UZIMA-DS:通过数据科学利用健康信息对东非产生有意义的影响
基本信息
- 批准号:10490293
- 负责人:
- 金额:$ 129万
- 依托单位:
- 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:
- 关键词:AddressAdolescentAdolescent and Young AdultAfricaAfricanAgeArtificial IntelligenceAssimilationsBiologicalCaringChildChild HealthCohort StudiesCommunicationCommunitiesCountryCoupledDataData AnalysesData AnalyticsData ScienceData SetData SourcesDepression and SuicideDevelopmentDevelopmental Delay DisordersEcosystemEnsureEnvironmentEventFAIR principlesFeeling suicidalFemale of child bearing ageFosteringFundingFutureFuture GenerationsGovernmentGrantGuidelinesHealthHealth PersonnelHealth systemHealthcareHigh Risk WomanHospitalsIndividualInformaticsInfrastructureInstitutesKenyaLeadLifeLow Birth Weight InfantMaternal HealthMaternal and Child HealthMedical ResearchMental DepressionMental HealthMethodsMichiganModelingMoodsMothersOutcomePathway interactionsPatternPersonal SatisfactionPilot ProjectsPoliciesPopulationPregnancy OutcomePrivate SectorReproducibilityResearchResearch InstituteResearch PersonnelResearch Project GrantsResearch SupportResearch TrainingResource-limited settingResourcesRiskSystemTraining ProgramsTrustUnited States National Institutes of HealthUniversitiesWomanWorkYouthantenatalcardiovascular disorder riskcare deliverycareerclinically relevantcommercializationcomputational platformcomputer sciencedata ecosystemdata hubdata interoperabilitydata managementdata sharingearly childhoodhigh riskimprovedmHealthmachine learning methodmachine learning predictionmobile applicationmobile computingmultidisciplinarymultimodal dataneonatal healthnovelnovel strategiesopen datapopulation healthpredictive modelingpregnancy hypertensionprogramspsychosocialrisk prediction modelstatisticssurveillance datasynergismtranslational pipelineuniversity studentyoung adult
项目摘要
PROJECT SUMMARY – Overall Component
Africa is the youngest continent in the world, with 60% of its population under the age of 25. The span between
early life to young adulthood represents a critical window where biological, environment and psychosocial events
can significantly impact long- term uzima, which means health/well-being in Swahili. Coupled with the recent
technological advances and the enormous volumes of data collected in Africa, there is an unprecedented
opportunity to leverage data science to identify and improve the health trajectories of young Africans. However,
significant analytical and computational barriers persist that impede our ability to use this information to change
care at the community and individual level. Our proposed Research Hub, UZIMA-DS, aims to change this
narrative by UtiliZing health Information for Meaningful impact in East Africa through Data Science. We will create
a scalable and sustainable platform to apply novel approaches to data assimilation and advanced artificial
intelligence (AI)/machine learning (ML)-based methods to serve as early warning systems to address critical
health issues impacting young Africans in two domains: maternal, newborn and child health and mental
health. Our Hub addresses three critical needs across the translational spectrum of data science: 1)
Harmonization of multimodal data sources for meaningful use and analyses; 2) Leveraging temporal patterns of
data to identify trajectories through prediction modeling using AI/ML-based methods; and 3) Engaging with key
stakeholders to identify pathways for dissemination and sustainability of these models into target communities.
For our Maternal and Child Health Study (Project 1), we will leverage the large and diverse existing data sets in
Kenya, including two demographic surveillance systems, cohort studies and hospital data, to develop and
validate AI/ML-based prediction models to identify women of childbearing age at high risk for poor pregnancy
outcomes (e.g., pregnancy-induced hypertension, low birthweight) and non-communicable diseases later in life
and children at risk of future poor life outcomes (e.g., developmental delays). For our Mental Health Study
(Project 2), leverage existing surveillance data as well as novel mobile technologies (e.g., mobile apps,
wearables) for the development of existing and new AI/ML-based prediction models to identify adolescents and
young healthcare workers at risk of depression and suicide ideation in Kenya. Our Hub and Projects will be
supported by an Admin Core, Data Management and Analysis Core, and a Dissemination and Sustainability
Core, which will facilitate engagement with multisectoral stakeholders to identify sustainable model dissemination
pathways into target communities. Ultimately, our work will empower African researchers to carry forward the
UZIMA-DS Hub to address on-going and evolving health needs of Africans by building sustainable infrastructure,
expertise, and partnerships for long-lasting impact. The UZIMA-DS Hub can serve as a model that can be scaled
to other countries and health domains with the greater DS-I consortium to transform care delivery in Africa,
ensuring that current and future generations of Africans can achieve uzima.
项目总结-整体组件
非洲是世界上最年轻的大陆,60%的人口年龄在25岁以下。之间的跨度
从生命早期到青年期是一个关键的窗口,
可以显著影响长期的uzima,这意味着斯瓦希里语的健康/福祉。加上近期
技术进步和在非洲收集的大量数据,
利用数据科学来识别和改善非洲年轻人的健康轨迹。然而,在这方面,
重要的分析和计算障碍仍然存在,阻碍了我们利用这些信息进行改变的能力
在社区和个人层面上的关怀。我们提议的研究中心UZIMA-DS旨在改变这一点
通过数据科学利用健康信息对东非产生有意义的影响。我们将创建
一个可扩展和可持续的平台,应用新的方法进行数据同化和先进的人工智能。
智能(AI)/机器学习(ML)的方法,作为早期预警系统,以解决关键的
在两个领域影响非洲青年的健康问题:孕产妇、新生儿和儿童健康以及心理健康
健康我们的中心解决了数据科学转化领域的三个关键需求:1)
协调多模式数据源,以便进行有意义的使用和分析; 2)利用
使用基于AI/ML的方法通过预测建模来识别轨迹的数据;以及3)与关键人物接触
利益攸关方确定向目标社区传播这些模式并使其可持续的途径。
对于我们的母婴健康研究(项目1),我们将利用现有的大型和多样化的数据集,
肯尼亚,包括两个人口监测系统、队列研究和医院数据,以发展和
验证基于AI/ML的预测模型,以识别处于不良妊娠高风险的育龄妇女
结果(例如,妊娠高血压、低出生体重)和非传染性疾病
以及面临未来不良生活后果风险的儿童(例如,发育迟缓)。我们的心理健康研究
(项目2),利用现有的监测数据以及新颖的移动的技术(例如,移动的应用程序,
可穿戴设备)用于开发现有的和新的基于AI/ML的预测模型,以识别青少年,
在肯尼亚,年轻的医护人员面临抑郁和自杀意念的风险。我们的中心和项目将是
由一个管理核心、数据管理和分析核心以及一个传播和可持续发展中心提供支持。
核心,将促进与多部门利益攸关方的接触,以确定可持续的模式传播
进入目标社区的途径。最终,我们的工作将使非洲研究人员能够发扬
UZIMA-DS Hub通过建设可持续的基础设施,满足非洲人持续和不断变化的健康需求,
专业知识和伙伴关系,以产生持久的影响。UZIMA-DS Hub可以作为可扩展的模型
与更大的DS-I联盟合作,向其他国家和卫生领域提供服务,以改变非洲的医疗服务,
确保当代和后代非洲人能够实现uzima。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Amina Abubakar Ali其他文献
Amina Abubakar Ali的其他文献
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{{ truncateString('Amina Abubakar Ali', 18)}}的其他基金
2/3 Akili: Phenotypic and genetic characterization of ADHD in Kenya and South Africa
2/3 Akili:肯尼亚和南非 ADHD 的表型和遗传特征
- 批准号:
10637187 - 财政年份:2023
- 资助金额:
$ 129万 - 项目类别:
Eneza Data Science: Enhancing Data Science Capability and Tools for Health in East Africa
Eneza 数据科学:增强东非健康领域的数据科学能力和工具
- 批准号:
10713044 - 财政年份:2023
- 资助金额:
$ 129万 - 项目类别:
UZIMA-DS: UtiliZing health Information for Meaningful impact in East Africa through Data Science
UZIMA-DS:通过数据科学利用健康信息对东非产生有意义的影响
- 批准号:
10659241 - 财政年份:2021
- 资助金额:
$ 129万 - 项目类别:
Improving AI/ML-readiness of Synthetic Data in a Resource-Constrained Setting
在资源受限的环境中提高合成数据的 AI/ML 准备度
- 批准号:
10841728 - 财政年份:2021
- 资助金额:
$ 129万 - 项目类别:
UZIMA-DS: UtiliZing health Information for Meaningful impact in East Africa through Data Science
UZIMA-DS:通过数据科学利用健康信息对东非产生有意义的影响
- 批准号:
10314084 - 财政年份:2021
- 资助金额:
$ 129万 - 项目类别:
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