Visual Analytics to Support Treatment Decisions in Late-Stage Melanoma Patients

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dc.contributor.authorPereira, Calidaen_US
dc.contributor.authorNiemann, Ulien_US
dc.contributor.authorBraun, Andreasen_US
dc.contributor.authorMengoni, Miriamen_US
dc.contributor.authorTüting, Thomasen_US
dc.contributor.authorPreim, Bernharden_US
dc.contributor.authorMeuschke, Moniqueen_US
dc.contributor.editorHansen, Christianen_US
dc.contributor.editorProcter, Jamesen_US
dc.contributor.editorRenata G. Raidouen_US
dc.contributor.editorJönsson, Danielen_US
dc.contributor.editorHöllt, Thomasen_US
dc.date.accessioned2023-09-19T11:31:43Z
dc.date.available2023-09-19T11:31:43Z
dc.date.issued2023
dc.description.abstractWe present a visual analytics system to support treatment decisions in late-stage Melanoma patients. With the aim of improving patient outcomes, personalized treatment decisions based on individual characteristics and medical histories are crucial. The research focuses on the design and development of a visual analytics system tailored specifically for tumor boards, where multidisciplinary teams collaborate to make informed decisions. By leveraging a comprehensive database containing treatment and tumor stage progression information from over 1100 patients, the system provides healthcare professionals with a holistic overview and facilitates the analysis of individual cases as well as comparisons between multiple patients. The distinction between tumor board preparation systems and systems used during discussions is emphasized to ensure user-centric design and usability. Through the use of visual analytics techniques, complex relationships between treatment outcomes, temporal features, and patient-specific factors are explored, enabling clinicians to identify patterns and trends that may impact treatment decisions. The findings of this research contribute to the growing field of visual analytics in healthcare and have the potential to enhance treatment decision-making and patient care in late-stage cancer scenarios.en_US
dc.description.sectionheadersDecision Making and Surgery Planning
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicine
dc.identifier.doi10.2312/vcbm.20231207
dc.identifier.isbn978-3-03868-216-5
dc.identifier.issn2070-5786
dc.identifier.pages1-11
dc.identifier.pages11 pages
dc.identifier.urihttps://doi.org/10.2312/vcbm.20231207
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vcbm20231207
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Human-centered computing -> Visualization; Computing methodologies -> Computer graphics
dc.subjectHuman centered computing
dc.subjectVisualization
dc.subjectComputing methodologies
dc.subjectComputer graphics
dc.titleVisual Analytics to Support Treatment Decisions in Late-Stage Melanoma Patientsen_US
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VCBM 2023: Eurographics Workshop on Visual Computing for Biology and Medicine