A clinical grid infrastructure supporting adverse hypotensive event prediction
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Author
STELL, ANTHONY; SINNOTT, RICHARD; Jiang, JipuDate
2009Source Title
9th IEEE/ACM International Symposium on Cluster Computing and the GridPublisher
IEEE Computer SocietyMetadata
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Conference PaperCitations
Stell, A., Sinnott, R., & Jiang, J. (2009). A clinical grid infrastructure supporting adverse hypotensive event prediction. In 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, Shanghai, China.Access Status
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Abstract
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.
Keywords
hypotension; data-grids; performance; securityExport Reference in RIS Format
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