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Multitask Gaussian processes for multivariate physiological time-series analysis.

Abstract:

Gaussian process (GP) models are a flexible means of performing nonparametric Bayesian regression. However, GP models in healthcare are often only used to model a single univariate output time series, denoted as single-task GPs (STGP). Due to an increasing prevalence of sensors in healthcare settings, there is an urgent need for robust multivariate time-series tools. Here, we propose a method using multitask GPs (MTGPs) which can model multiple correlated multivariate physiological time ser...

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Publication status:
Published
Peer review status:
Peer reviewed

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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:
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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Funding agency for:
Pimentel, M
Grant:
Digital Economy Program
EP/G036861/1
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Funding agency for:
Pimentel, M
Grant:
Digital Economy Program
EP/G036861/1
More from this funder
Funding agency for:
Clifton, D
Grant:
Centre of Excellence in Personalized Healthcare; WT 088877/Z/09/Z
More from this funder
Funding agency for:
Clifton, D
Grant:
Centre of Excellence in Personalized Healthcare; WT 088877/Z/09/Z
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Publisher:
IEEE Publisher's website
Publication date:
2015-01-01
DOI:
EISSN:
1558-2531
ISSN:
0018-9294
Source identifiers:
504520
Language:
eng
Keywords:
Pubs id:
pubs:504520
UUID:
uuid:13522376-845d-41e8-9fc8-81a17d33e2d6
Local pid:
pubs:504520
Deposit date:
2016-01-18

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