@neurIST infrastructure for advanced disease management through integration of heterogeneous data, computing, and complex processing services

Citació

  • Benkner S, Arbona A, Berti G, Chiarini A, Dunlop R, Engelbrecht G, Frangi A F, Friedrich C M, Hanser S, Hasselmeyer P, Hose R D, Iavindrasana J, Köhler M, Iacono L L, Lonsdale G, Meyer R, Moore B, Rajasekaran H, Summers P E, Wöhrer A, Wood S. @neurIST Infrastructure for Advanced Disease Management through Integration of Heterogeneous Data, Computing, and Complex Processing Services. IEEE Transactions on Information Technology in Biomedicine. 2010;14(6):1365-1377. DOI 10.1109/TITB.2010.2049268
    Benkner S, Arbona A, Berti G, Chiarini A, Dunlop R, Engelbrecht G, Frangi AF et al. @neurIST infrastructure for advanced disease management through integration of heterogeneous data, computing, and complex processing services. IEEE Trans Inf Technol Biomed. 2010; 14(6): 1365-1377. DOI 10.1109/TITB.2010.2049268

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  • Resum

    The increasing volume of data describing human/ndisease processes and the growing complexity of understanding, managing, and sharing such data presents a huge challenge for clinicians and medical researchers. This paper presents the/n@neurIST system, which provides an infrastructure for biomedical research while aiding clinical care, by bringing together heterogeneous data and complex processing and computing services. Although @neurIST targets the investigation and treatment of cerebral aneurysms, the system’s architecture is generic enough that it could be adapted to the treatment of other diseases./nInnovations in @neurIST include confining the patient data pertaining to aneurysms inside a single environment that offers clinicians/nthe tools to analyze and interpret patient data and make use of knowledge-based guidance in planning their treatment. Medical/nresearchers gain access to a critical mass of aneurysm related data due to the system’s ability to federate distributed information/nsources. A semantically mediated grid infrastructure ensures that both clinicians and researchers are able to seamlessly access and/nwork on data that is distributed across multiple sites in a secure way in addition to providing computing resources on demand for/nperforming computationally intensive simulations for treatment planning and research.
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