Visual Analytics for Epidemiology

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dc.contributor.authorPreim, Bernharden_US
dc.contributor.authorAlemzadeh, Shivaen_US
dc.contributor.authorIttermann, Tillen_US
dc.contributor.authorKlemm, Paulen_US
dc.contributor.authorNiemann, Ulien_US
dc.contributor.authorSpiliopoulou, Myraen_US
dc.contributor.editorBruckner, Stefan and Oeltze-Jafra, Steffenen_US
dc.date.accessioned2019-05-05T17:45:22Z
dc.date.available2019-05-05T17:45:22Z
dc.date.issued2019
dc.description.abstractWe present visual analytics methods to analyze epidemiologic cohort studies. We consider the automatic identification of strong correlations and of subgroups that deviate from the global mean with respect to their risk for health disorders. Moreover, we tackle missing value problems and discuss appropriate imputation strategies and visual analytics support.en_US
dc.description.sectionheaders3rd Prize
dc.description.seriesinformationEurographics 2019 - Dirk Bartz Prize
dc.identifier.doi10.2312/egm.20191034
dc.identifier.issn1017-4656
dc.identifier.pages9-12
dc.identifier.urihttps://doi.org/10.2312/egm.20191034
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/egm20191034
dc.publisherThe Eurographics Associationen_US
dc.subjectJ.3 [Computer Graphics]
dc.subjectComputer Applications
dc.titleVisual Analytics for Epidemiologyen_US
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