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dc.contributor.authorFederico, Paoloen_US
dc.contributor.authorUnger, Jürgenen_US
dc.contributor.authorAmor-Amorós, Alberten_US
dc.contributor.authorSacchi, Luciaen_US
dc.contributor.authorKlimov, Denisen_US
dc.contributor.authorMiksch, Silviaen_US
dc.contributor.editorE. Bertini and J. C. Robertsen_US
dc.date.accessioned2015-05-24T19:45:52Z
dc.date.available2015-05-24T19:45:52Z
dc.date.issued2015en_US
dc.identifier.urihttp://dx.doi.org/10.2312/eurova.20151108en_US
dc.description.abstractThe advanced visualization of electronic health records (EHRs), supporting a scalable analysis from single patients to cohorts, intertwining patients' conditions with executed treatments, and handling the complexity of timeoriented data, is an open challenge of visual analytics for health care. We propose an approach that, according to the knowledge-assisted visualization paradigm, leverages the domain knowledge acquired by clinical experts and formalized into computer-interpretable guidelines (CIGs), in order to improve the automated analysis, the visualization, and the interactive exploration of EHRs of patient cohorts. In this way, the analyst can get insights about the clinical history of multiple patients and assess the effectiveness of their health care treatments.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectJ.3 [Computer applications]en_US
dc.subjectLife and medical scienceen_US
dc.subjectMedical information systemsen_US
dc.titleGnaeus: Utilizing Clinical Guidelines for Knowledge-assisted Visualisation of EHR Cohortsen_US
dc.description.seriesinformationEuroVis Workshop on Visual Analytics (EuroVA)en_US
dc.description.sectionheadersTime-series and Temporal Dataen_US
dc.identifier.doi10.2312/eurova.20151108en_US
dc.identifier.pages79-83en_US


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