uu.seUppsala University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Federating distributed clinical data for the prediction of adverse hypotensive events
Show others and affiliations
2009 (English)In: Philosophical Transactions. Series A: Mathematical, physical, and engineering science, ISSN 1364-503X, E-ISSN 1471-2962, Vol. 367, no 1898, 2679-2690 p.Article in journal (Refereed) Published
Abstract [en]

The ability to predict adverse hypotensive events, where a patient's arterial blood pressure drops to abnormally low (and dangerous) levels, would be of major benefit to the fields of primary and secondary health care, and especially to the traumatic brain injury domain. A wealth of data exist in health care systems providing information on the major health indicators of patients in hospitals (blood pressure, temperature, heart rate, etc.). It is believed that if enough of these data could be drawn together and analysed in a systematic way, then a system could be built that will trigger an alarm predicting the onset of a hypotensive event over a useful time scale, e.g. half an hour in advance. In such circumstances, avoidance measures can be taken to prevent such events arising. This is the basis for the Avert-IT project (http://www.avert-it.org), a collaborative EU-funded project involving the construction of a hypotension alarm system exploiting Bayesian neural networks using techniques of data federation to bring together the relevant information for study and system development.

Place, publisher, year, edition, pages
2009. Vol. 367, no 1898, 2679-2690 p.
Keyword [en]
data federation, hypotension prediction, clinical grids
National Category
Surgery Neurosciences
Research subject
Neurosurgery
Identifiers
URN: urn:nbn:se:uu:diva-123078DOI: 10.1098/rsta.2009.0042ISI: 000267281800007PubMedID: 19487204OAI: oai:DiVA.org:uu-123078DiVA: diva2:311795
Available from: 2010-04-23 Created: 2010-04-23 Last updated: 2017-12-12Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textPubMed
By organisation
Neurosurgery
In the same journal
Philosophical Transactions. Series A: Mathematical, physical, and engineering science
SurgeryNeurosciences

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 335 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf