Monitoring patient vital-sign deterioration trajectories using Bayesian inference

Conference item

Vital signs recorded at the hospital bedside manually by clinical staff are key indicators of patient physiology and may be used to track patient deterioration. The low frequency of vital-sign observations by clinical staff (every 4, 8 or 12 hours) makes it difficult to determine the underlying distribution for each vital sign. In this paper we demonstrate how a Bayesian approach may be used to estimate the unknown parameters of vital sign data.

Authors: Khalid, S; Clifton, D; Tarassenko, L

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: IEEE
• Host title: Proceedings of the 6th UKRI PG Conference in Biomedical Engineering and Medical Physics 2011
• Journal: Proceedings of the 6th UKRI PG Conference in Biomedical Engineering and Medical Physics 2011
• Pages: 1
• Publication date: 2011-08-01
• Acceptance date: 2011-08-01
• Event location: Glasgow
• Keywords: SBTMR