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Thesis

Modelling of vital-sign data from post-operative patients

Alternative title:
Machine learning approach to patient monitoring
Abstract:

Thousands of in-hospital deaths each year in the UK are potentially preventable, being often preceded by physiological deterioration. The current standard of clinical practice for patient monitoring on general wards is the periodic observation of vital signs by nursing staff. The use of early warning score (EWS) systems should enable a more timely response to, and assessment of, acutely ill patients. The investigations described in this thesis seek to apply principled approaches based on m...

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author

Contributors

Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Supervisor
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Supervisor
Department:
John Radcliffe Hospital, University of Oxford
Role:
Examiner
Department:
Institute for Adaptive and Neural Computation, University of Edinburgh
Role:
Examiner
NIHR Biomedical Research Centre Programme More from this funder
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford

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