A clinical grid infrastructure supporting adverse hypotensive event prediction

Stell, A.J., Sinnott, R.O. and Jiang, J. (2009) A clinical grid infrastructure supporting adverse hypotensive event prediction. In: Cappello, F., Wang, C.L. and Buyya, R. (eds.) 9th IEEE/ACM International Symposium on Cluster Computing and the Grid CCGrid 2009, Shanghai, China, May 18-21, 2009. IEEE Computer Society: Los Alamitos, USA, pp. 508-513. ISBN 9781424439355 (doi: 10.1109/CCGRID.2009.43)

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.

• Item Type: Book Sections
• Keywords: Data-Grids, hypotension, performance, security
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Stell, Mr Anthony and Jiang, Mr Jipu and Sinnott, Professor Richard
• Authors: Stell, A.J., Sinnott, R.O., and Jiang, J.
• Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
• College/School: University Services > IT Services > Computing Service
• Publisher: IEEE Computer Society
• ISBN: 9781424439355
• Copyright Holders: Copyright © 2009 IEEE Computer Society
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher.