Computing and Information Systems - Research Publications

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    A distributed clinical data platform for physiological studies in the brain trauma domain
    STELL, ANTHONY ; SINNOTT, RICHARD ; Donald, Rob ; Chambers, Iain ; Citerio, Giuseppe ; Enblad, Per (IEEE Computer Society, 2010)
    There are many serious and acute physiological conditions about which we have incomplete medical knowledge that can support optimal healthcare intervention. To develop effective treatments a wealth of clinical data is required for collection, analysis and feedback. Such data often does exist but is typically held in a variety of different formats and locations. This paper describes the EU FP7-funded Avert-IT project (www.avert-it.org), which has developed an integrated, real-time physiological data grid infrastructure (HypoNet) to address the specific issue of prediction of hypotensive events in the brain trauma domain and is currently being used as part of a large multi-centre clinical trial. The implementation and application of the HypoNet system is described here.
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    A clinical grid infrastructure supporting adverse hypotensive event prediction
    STELL, ANTHONY ; SINNOTT, RICHARD ; Jiang, Jipu (IEEE Computer Society, 2009)
    The condition of hypotension - where a person's arterial blood pressure drops to an abnormally low level - is a common and potentially fatal occurrence in patients under intensive care. As medical interventions to treat such events are typically reactive and often aggressive, there would be great benefit in having a prediction system that can warn health-care professionals of an impending event and thereby allow them to provide non-invasive, preventative treatments. This paper describes the progress of the EU FP7 funded Avert-IT project, which is developing just such a system using Bayesian neural network learning technology based upon an integrated, real-time data grid infrastructure, which draws together heterogeneous data-sets from six clinical centres across Europe.