Detection of Diabetic Neuropathy - Can Visual Analytics Methods Really Help in Practice?

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dc.contributor.authorRöhlig, Martinen_US
dc.contributor.authorStachs, Oliveren_US
dc.contributor.authorSchumann, Heidrunen_US
dc.contributor.editorKai Lawonn and Mario Hlawitschka and Paul Rosenthalen_US
dc.date.accessioned2016-06-09T09:31:52Z
dc.date.available2016-06-09T09:31:52Z
dc.date.issued2016en_US
dc.description.abstractVisual analytics (VA) methods are valuable means for supporting the detection of diabetic neuropathy, the most common longterm complication of diabetes mellitus. We suggest two strategies for strengthening reliability, reproducibility, and applicability of dedicated VA methods in practice. First, we introduce a novel workflow visualization that shows activities together with metadata and produced output, facilitating a guided step-wise analysis. Second, we present a tailored user interface that integrates various VA tools, unifying access to their functionality and enabling free exploration for further assisting the medical diagnosis. By applying both strategies, we effectively enhance the practical utility of our VA approach for detecting diabetic neuropathy.en_US
dc.description.sectionheadersVisual Analytics and Storytelling in Medical Visualizationen_US
dc.description.seriesinformationEuroVis Workshop on Reproducibility, Verification, and Validation in Visualization (EuroRV3)en_US
dc.identifier.doi10.2312/eurorv3.20161111en_US
dc.identifier.isbn978-3-03868-017-8en_US
dc.identifier.issn-en_US
dc.identifier.issn1017-4656en_US
dc.identifier.pages19-21en_US
dc.identifier.urihttps://doi.org/10.2312/eurorv3.20161111en_US
dc.identifier.urihttps://diglib.eg.org:443/handle/10
dc.publisherThe Eurographics Associationen_US
dc.subjectHumanen_US
dc.subjectcentered computingen_US
dc.subjectVisualizationen_US
dc.subjectVisualization application domainsen_US
dc.subjectVisual analyticsen_US
dc.titleDetection of Diabetic Neuropathy - Can Visual Analytics Methods Really Help in Practice?en_US
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