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A novel method of combining local and global data sources to estimate local impact of behavioral interventions on disease burden

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dc.contributor.advisorAli, Özden Gür
dc.contributor.departmentGraduate School of Sciences and Engineering
dc.contributor.kuauthorGhanem, Angi Nazih
dc.contributor.programIndustrial Engineering
dc.contributor.schoolcollegeinstituteGRADUATE SCHOOL OF SCIENCES AND ENGINEERING
dc.coverage.spatialİstanbul
dc.date.accessioned2024-11-09T21:57:15Z
dc.date.issued2019
dc.format.extentxxii, 284 leaves : illustratios ; 30 cm.
dc.identifier.urihttps://hdl.handle.net/20.500.14288/4495
dc.language.isoeng
dc.publisherKoç University
dc.relation.collectionKU Theses and Dissertations
dc.rightsrestrictedAccess
dc.rights.copyrightsnote© All Rights Reserved. Accessible to Koç University Affiliated Users Only!
dc.subjectBayesian statistical decision theory
dc.subjectMachine learning
dc.subjectStatistical decision
dc.subjectHealthcare
dc.subjectHierarchical bayesian model
dc.subjectBurden of disease
dc.subjectBehavioral interventions impact
dc.subjectTargeting
dc.subjectPublic health
dc.subjectPolicy evaluation
dc.subjectPredictive
dc.subjectDomain knowledge
dc.subjectData science
dc.titleA novel method of combining local and global data sources to estimate local impact of behavioral interventions on disease burden
dc.typeDissertation
dspace.entity.typePublication
local.contributor.kuauthorGhanem, Angi Nazih
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