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dc.contributor.authorSteinhauer, Nastasjaen_US
dc.contributor.authorHörbrugger, Marcen_US
dc.contributor.authorBraun, Andreas Dominiken_US
dc.contributor.authorTüting, Thomasen_US
dc.contributor.authorOeltze-Jafra, Steffenen_US
dc.contributor.authorMüller, Julianeen_US
dc.contributor.editorKerren, Andreas and Garth, Christoph and Marai, G. Elisabetaen_US
dc.date.accessioned2020-05-24T13:52:17Z
dc.date.available2020-05-24T13:52:17Z
dc.date.issued2020
dc.identifier.isbn978-3-03868-106-9
dc.identifier.urihttps://doi.org/10.2312/evs.20201067
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/evs20201067
dc.description.abstractIn multidisciplinary oncological team meetings for patient-specific treatment decision-making, so-called tumor boards, usually one physician introduces a patient case verbally and proposes an initial therapy recommendation. This is followed by a short collaborative discussion of the recommendation's suitability. While patient-related image data, such as CT and MR scans, are displayed during the discussion, clinical patient data must be memorized from the introduction or repeatedly inquired by the participating domain experts. To support physicians in this concern, we propose a comprehensive visualization of longitudinal patient-specific information entities during case introduction and discussion. Our visual approach advances over existing work by simultaneously providing an overview of the current patient status as well as of previous therapy measures and their effects on the status. The latter assists in relating the currently proposed recommendation to the previous treatment measures and the related patient status. The visualization has been designed in close collaboration with dermatologists and oncologists aiming at a comprehensive yet easily comprehensible presentation of relevant patient-data and minimal user interaction. The usability and clinical relevance of the prototypical implementation of our visual approach have been evaluated in a qualitative user study with five domain experts based on real anonymized data of melanoma patients.en_US
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/]
dc.subjectApplied computing
dc.subjectHealth care information systems
dc.subjectHuman centered computing
dc.subjectInformation visualization
dc.titleComprehensive Visualization of Longitudinal Patient Data for the Dermatological Oncological Tumor Boarden_US
dc.description.seriesinformationEuroVis 2020 - Short Papers
dc.description.sectionheadersRendering, Images, and Applications
dc.identifier.doi10.2312/evs.20201067
dc.identifier.pages169-173


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Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Attribution 4.0 International License