A Clinical Grid Infrastructure Supporting Adverse Hypotensive Event Prediction

  • Authors:
  • Anthony Stell;Richard Sinnott;Jipu Jiang

  • Affiliations:
  • -;-;-

  • Venue:
  • CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
  • Year:
  • 2009

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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.