Palleschi, AlessiaPetti, ManuelaTieri, PaoloAngelini, MarcoBernard, JürgenAngelini, Marco2022-06-022022-06-022022978-3-03868-183-02664-4487https://doi.org/10.2312/eurova.20221075https://diglib.eg.org:443/handle/10.2312/eurova20221075The 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.Attribution 4.0 International LicenseCCS Concepts: Human-centered computing --> Visual analytics; Applied computing --> Computational genomics; Biological networksHuman centered computingVisual analyticsApplied computingComputational genomicsBiological networksToward Disease Diagnosis Visual Support Bridging Classic and Precision Medicine10.2312/eurova.2022107525-295 pages