Comprehensive Visualization of Longitudinal Patient Data for the Dermatological Oncological Tumor Board
dc.contributor.author | Steinhauer, Nastasja | en_US |
dc.contributor.author | Hörbrugger, Marc | en_US |
dc.contributor.author | Braun, Andreas Dominik | en_US |
dc.contributor.author | Tüting, Thomas | en_US |
dc.contributor.author | Oeltze-Jafra, Steffen | en_US |
dc.contributor.author | Müller, Juliane | en_US |
dc.contributor.editor | Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta | en_US |
dc.date.accessioned | 2020-05-24T13:52:17Z | |
dc.date.available | 2020-05-24T13:52:17Z | |
dc.date.issued | 2020 | |
dc.description.abstract | In 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.description.sectionheaders | Rendering, Images, and Applications | |
dc.description.seriesinformation | EuroVis 2020 - Short Papers | |
dc.identifier.doi | 10.2312/evs.20201067 | |
dc.identifier.isbn | 978-3-03868-106-9 | |
dc.identifier.pages | 169-173 | |
dc.identifier.uri | https://doi.org/10.2312/evs.20201067 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/evs20201067 | |
dc.publisher | The Eurographics Association | en_US |
dc.rights | Attribution 4.0 International License | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | ] |
dc.subject | Applied computing | |
dc.subject | Health care information systems | |
dc.subject | Human centered computing | |
dc.subject | Information visualization | |
dc.title | Comprehensive Visualization of Longitudinal Patient Data for the Dermatological Oncological Tumor Board | en_US |
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