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Distributed Contextualization of Biomedical Data: a case study in precision medicine

Abstract : An important aspect of precision medicine consists in patient-centered contextualization analyses that are used as part of biomedical interactive tools. Such analyses often harness data of large populations of patients from different research centers and can often benefit from a distributed implementation. However, performance and the security and privacy concerns of sharing sensitive biomedical data can become a major issue. We have investigated these issues in the context of a kidney transplanted patient contextualization project: the Kidney Transplantation Application (KITAPP). In this paper, we present a motivation for distributed implementations in this context, notably for computing percentiles for contextualization. We present a corresponding system architecture, motivate privacy and performance issues, and present a novel distributed implementation that is evaluated in a realistic multi-site setting.
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Submitted on : Wednesday, August 26, 2020 - 4:22:12 PM
Last modification on : Friday, January 21, 2022 - 3:09:59 AM
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Sirine Sayadi, Estelle Geffard, Mario Südholt, Nicolas Vince, Pierre-Antoine Gourraud. Distributed Contextualization of Biomedical Data: a case study in precision medicine. AICCSA 2020 - 17th IEEE/ACS International Conference on Computer Systems and Applications, Nov 2020, Antalya, Turkey. pp.1-6, ⟨10.1109/AICCSA50499.2020.9316502⟩. ⟨hal-02922930⟩



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