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Bayesian optimisation of Gaussian processes for identifying the deteriorating patient

Abstract:

Patient deterioration in the hospital ward is typically preceded by several hours of deranged physiology, as measured by the patient’s vital signs. Estimation of the expected trajectory of a patient’s future vital signs can allow us determine the degree of risk of physiological deterioration for that patient. Gaussian processes (GPs) offer a principled means of estimating vital-sign trajectories within a probabilistic framework. The automated estimation of GP parameters in this setting is dif...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/BHI.2017.7897211

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Institution:
University of Oxford
Oxford college:
St Cross College
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:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
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Funding agency for:
Colopy, G
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Funding agency for:
Pimentel, M
Grant:
HAVEN project, WT 103703/Z/14/Z
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Funding agency for:
Clifton, D
Grant:
Challenge Award
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Funding agency for:
Clifton, D
Grant:
Challenge Award
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Publisher:
IEEE Publisher's website
Journal:
EEE International Conference on Biomedical and Health Informatics Journal website
Pages:
85-88
Host title:
2017 IEEE International Conference on Biomedical and Health Informatics
Publication date:
2017-04-13
Acceptance date:
2017-01-13
DOI:
ISSN:
2168-2194
Source identifiers:
682581
ISBN:
9781509041794
Pubs id:
pubs:682581
UUID:
uuid:c8b4a82d-0418-4e84-a1cf-54257efb6573
Local pid:
pubs:682581
Deposit date:
2017-03-01

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