@neurIST -- Infrastructure for Advanced Disease Management through Integration of Heterogeneous Data, Computing, and Complex Processing Services

Siegfried Benkner, Antonio Arbona, Guntram Berti, Alessandro Chiarini, Robert Dunlop, Gerhard Engelbrecht, Alejandro F. Frangi, Christoph M. Friedrich, Susanne Hanser, Peer Hasselmeyer, Rod D. Hose, Jimison Iavindrasana, Martin Köhler, Luigi Lo Iacono, Guy Lonsdale, Rodolphe Meyer, Bob Moore, Hariharan Rajasekaran, Paul E. Summers, Alexander Wöhrer, Steven Wood:
@neurIST -- Infrastructure for Advanced Disease Management through Integration of Heterogeneous Data, Computing, and Complex Processing Services IEEE Transactions on Information Technology in BioMedicine 14(6), pp. 1365-1377, November 2010.
The increasing volume of data describing human disease 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 @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. Innovations in @neurIST include confining the patient data pertaining to aneurysms inside a single environment that offers clinicians the tools to analyze and interpret patient data and make use of knowledge-based guidance in planning their treatment. Medical researchers gain access to a critical mass of aneurysm related data due to the system's ability to federate distributed information sources. A semantically mediated grid infrastructure ensures that both clinicians and researchers are able to seamlessly access and work on data that is distributed across multiple sites in a secure way in addition to providing computing resources on demand for performing computationally intensive simulations for treatment planning and research.