MetricScalpel: Analyzing Diagnostic Outcomes with Exploratory Data Visualization

dc.contributor.authorLi, Weien_US
dc.contributor.authorElderman, Joepen_US
dc.contributor.authorHoogerwoord, Erwinen_US
dc.contributor.authorFunk, Mathiasen_US
dc.contributor.authorBrombacher, Aarnout C.en_US
dc.contributor.editorTobias Isenberg and Filip Sadloen_US
dc.date.accessioned2016-06-09T09:33:30Z
dc.date.available2016-06-09T09:33:30Z
dc.date.issued2016en_US
dc.description.abstractHealthcare data is the emerging force to push ahead smarter clinical solutions. However, unforeseen challenges like unmanaged massive data and costly access to it make it difficult for domain experts to easily derive actionable insights. In collaboration with a local diagnostic service provider, we designed MetricScalpel, a web-based visualization tool to help people quickly look into the real-life diagnostic data in the local community. The tool enables swift exploration into the multivariate diagnostic data sets from different sources and facilitates data selection/subsetting for deeper analysis. It can be used to reveal overlooked health conditions on almost any level without the requirement of heavy technical knowledge. Such design makes it easier to be accepted by a wider user group in the healthcare related organizations. It was proven to well serve the domain experts in validating pre-exist hypotheses in cohort analysis as well as revealing undiscovered patterns of health conditions in the local community. External evaluation shows operation cost was remarkably confined as domain experts were assisted with direct and intuitive access to the relevant data in need.en_US
dc.description.sectionheadersPosteren_US
dc.description.seriesinformationEuroVis 2016 - Postersen_US
dc.identifier.doi10.2312/eurp.20161129en_US
dc.identifier.isbn978-3-03868-015-4en_US
dc.identifier.issn-en_US
dc.identifier.pages9-11en_US
dc.identifier.urihttps://doi.org/10.2312/eurp.20161129en_US
dc.identifier.urihttps://diglib.eg.org:443/handle/10
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.3 [Computer Graphics]en_US
dc.subjectPicture/Image Generationen_US
dc.subjectLine and curve generationen_US
dc.titleMetricScalpel: Analyzing Diagnostic Outcomes with Exploratory Data Visualizationen_US
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