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Utilisation of the signature method to identify the early onset of sepsis from multivariate physiological time series in critical care monitoring

Abstract:

Objectives: Patients in an ICU are particularly vulnerable to sepsis. It is therefore important to detect its onset as early as possible. This study focuses on the development and validation of a new signature-based regression model, augmented with a particular choice of the handcrafted features, to identify a patient’s risk of sepsis based on physiologic data streams. The model makes a positive or negative prediction of sepsis for every time interval since admission to the ICU. Design: Th...

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Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author
ORCID:
0000-0001-7938-370X
Publisher:
Lippincott, Williams & Wilkins
Journal:
Critical Care Medicine More from this journal
Volume:
48
Issue:
10
Pages:
e976-e981
Publication date:
2020-08-03
Acceptance date:
2020-04-16
DOI:
EISSN:
1530-0293
ISSN:
0090-3493
Language:
English
Keywords:
Pubs id:
1102746
Local pid:
pubs:1102746
Deposit date:
2020-05-04

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