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dc.contributor.authorKarall, Nikolausen_US
dc.contributor.authorGröller, Eduarden_US
dc.contributor.authorRaidou, Renata Georgiaen_US
dc.contributor.editorJimmy Johansson and Filip Sadlo and Tobias Schrecken_US
dc.date.accessioned2018-06-02T17:54:27Z
dc.date.available2018-06-02T17:54:27Z
dc.date.issued2018
dc.identifier.isbn978-3-03868-060-4
dc.identifier.urihttp://dx.doi.org/10.2312/eurovisshort.20181077
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/eurovisshort20181077
dc.description.abstractIn breast cancer chemotherapy treatment, different alternative strategies can be employed. Clinical researchers working on the optimization of chemotherapy strategies need to analyze the progress of the treatment and to understand how different groups of patients respond to selected therapies. This is a challenging task, because of the multitude of imaging and non-imaging health record data involved. We, hereby, introduce a web-based dashboard that facilitates the comparison and analysis of publicly available breast cancer chemotherapy response data, consisting of a follow-up study of 63 patients. Each patient received one of two available therapeutic strategies and their treatment response was documented. Our dashboard provides an initial basis for clinical researchers working on chemotherapy optimization, to analyze the progress of treatment and to compare the response of (groups of) patients with distinct treatment characteristics. Our approach consists of multiple linked representations that provide interactive views on different aspects of the available imaging and non-imaging data. To illustrate the functionality of the ChemoExplorer, we conducted a usage scenario that shows the initial results of our work.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectHuman
dc.subjectcentered computing
dc.subjectVisual analytics
dc.subjectApplied computing
dc.subjectLife and medical sciences
dc.titleChemoExplorer: A Dashboard for the Visual Analysis of Chemotherapy Response in Breast Cancer Patientsen_US
dc.description.seriesinformationEuroVis 2018 - Short Papers
dc.description.sectionheadersVisual Analytics and Applications
dc.identifier.doi10.2312/eurovisshort.20181077
dc.identifier.pages49-53


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