grant
Machine learning in publicly available geotagged data to allow monitoring of maternal and child health
Organization STANFORD UNIVERSITYLocation STANFORD, UNITED STATESPosted 21 Aug 2024Deadline 30 Apr 2029
NIHUS FederalResearch GrantFY20250-11 years oldAcute respiratory infectionAir PollutionAnemiaAreaAttentionBenchmarkingBest Practice AnalysisBig DataBigDataBirthCessation of lifeChargeChildChild MalnutritionChild MortalityChild UndernutritionChild YouthChildhoodChildhood Nutritional DeficiencyChildren (0-21)CodeCoding SystemCommunitiesConsumptionCountryDataData SetData SourcesDeathDeath RateDetectionDiarrheaDrugsElectricityEvaluationFamily PlanningFamily Planning ServicesFeverGeographic AreaGeographic LocationsGeographic RegionGeographical LocationGeographyHealthHealth Care FacilityHealth FacilitiesHealth StatusHouseholdHydrogen OxideImageImageryImpoverishedInfrastructureInterventionInvestigatorsKnowledgeLMICLeadLevel of HealthMachine LearningMapsMaternal MortalityMaternal and Child HealthMaternal-Child Health ServicesMeasurementMeasuresMedicationMethodsMinorityModelingMonitorNatureNeighborhoodsOutcomeParturitionPb elementPerformancePharmaceutical PreparationsPoliciesPolicy MakerPopulationPostnatal CarePovertyPrevalencePublic HealthPublicationsPyrexiaRegistriesResearchResearch PersonnelResearchersResolutionSamplingSanitationScienceScientific PublicationSeriesSourceSupplementationSurfaceSurvey InstrumentSurveysTechniquesTestingTimeTrainingTravelUncertaintyUpdateVaccinationValidationVitamin AWaterWomanantenatalantepartumbenchmarkcare facilitiescare servicescare systemschildbearing agechildren dietary deficiencycommunity level disadvantagecostdata resourcedata visualizationdisadvantaged communitydoubtdrug/agentfebrilefebrisfertile agegeographic sitehealth levelheavy metal Pbheavy metal leadimagingimaging approachimaging based approachimprovedinnovateinnovationinnovativekidslow and middle-income countriesmachine based learningmachine learning based modelmachine learning modelmaternal deathmortality ratemortality rationeighborhood barrierneighborhood disadvantageneighborhood-level barrierneighborhood-level disadvantagenew approachesnovelnovel approachesnovel strategiesnovel strategypediatricpost-natal careremote communitiesreproductive agereproductive yearsresolutionsskillssuccessvalidationswater qualityyoungster
Description preview
Over 95 percent of maternal and child deaths globally occur in low- and middle-income countries (LMICs)
where reliable death registries are mostly unavailable and other dependable data are scarce. Moreover, within
LMICs, the most disadvantaged and remote communities tend to have the highest mortality rates but the least
reliable data. Knowledge on…
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