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Identification of patient deterioration in vital-sign data using one-class support vector machines

Abstract:

Adverse hospital patient outcomes due to deterioration are often preceded by periods of physiological deterioration that is evident in the vital signs, such as heart rate, respiratory rate, etc. Clinical practice currently relies on periodic, manual observation of vital signs, which typically occurs every 2-to-4 hours in most hospital wards, and so patient deterioration may go unidentified. While continuous patient monitoring systems exist for those patients who are confined to a hospital bed...

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Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MSD
Department:
NDORMS
Sub department:
Centre for Statistics in Medicine
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
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Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
National Institute for Health Research Biomedical Research Centre Programme More from this funder
UK Goverment More from this funder
Publisher:
Institute of Electrical and Electronics Engineers Publisher's website
Pages:
125-131
Host title:
2011 Federated Conference on Computer Science and Information Systems, FedCSIS 2011
Publication date:
2011-12-14
Source identifiers:
306980
ISBN:
9781457700415
Keywords:
Pubs id:
pubs:306980
UUID:
uuid:04012ca1-40c4-4585-9a88-c9f245b81d2d
Local pid:
pubs:306980
Deposit date:
2013-11-17

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