Toward Disease Diagnosis Visual Support Bridging Classic and Precision Medicine

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dc.contributor.authorPalleschi, Alessiaen_US
dc.contributor.authorPetti, Manuelaen_US
dc.contributor.authorTieri, Paoloen_US
dc.contributor.authorAngelini, Marcoen_US
dc.contributor.editorBernard, Jürgenen_US
dc.contributor.editorAngelini, Marcoen_US
dc.date.accessioned2022-06-02T14:59:50Z
dc.date.available2022-06-02T14:59:50Z
dc.date.issued2022
dc.description.abstractThe traditional approach in medicine starts with investigating patients' symptoms to make a diagnosis. While with the advent of precision medicine, a diagnosis results from several factors that interact and need to be analyzed together. This added complexity asks for increased support for medical personnel in analyzing these data altogether. Our objective is to merge the traditional approach with network medicine to offer a tool to investigate together symptoms, anatomies, diseases, and genes to establish a diagnosis from different points of view. This paper aims to help the clinician with the typical workflow of disease analysis, proposing a Visual Analytics tool to ease this task. A use case demonstrates the benefits of the proposed solution.en_US
dc.description.sectionheadersApplications
dc.description.seriesinformationEuroVis Workshop on Visual Analytics (EuroVA)
dc.identifier.doi10.2312/eurova.20221075
dc.identifier.isbn978-3-03868-183-0
dc.identifier.issn2664-4487
dc.identifier.pages25-29
dc.identifier.pages5 pages
dc.identifier.urihttps://doi.org/10.2312/eurova.20221075
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/eurova20221075
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 --> Visual analytics; Applied computing --> Computational genomics; Biological networks
dc.subjectHuman centered computing
dc.subjectVisual analytics
dc.subjectApplied computing
dc.subjectComputational genomics
dc.subjectBiological networks
dc.titleToward Disease Diagnosis Visual Support Bridging Classic and Precision Medicineen_US
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