Name: Healthcare condition monitoring using ICU data
Start: 2017-11-16T18:30:00Z
End: 2017-11-16T21:30:00Z
Location: QuantumBlack

Professor Chris Williams from the University of Edinburgh will discuss research aimed at improving ICU patient care using condition monitoring. This is often impeded by the presence of artifacts in the data; maintaining blood pressure in critically ill patients is a key management goal and yet it is the physiological variable most prone to error.

Using data from vital signs data collected from the Neuro ICU at the Southern General Hospital, Glasgow, Chris will describe work on using the the Factorial Switching Linear Dynamical System (FSLDS) and the Discriminative Switching Linear Dynamical System (DSLDS) for the detection, removal and cleaning of artifacts.

Chris will also present a non-linear dynamical system for modelling the effect of drug infusions on the vital signs of patients admitted in Intensive Care Units (ICUs). More specifically the work is interested in modelling the effect of a widely used anaesthetic drug called Propofolon a patient's monitored depth of anaesthesia and haemodynamics. The approach is compared with one from the Pharmacokinetics/Pharmacodynamics (PK/PD) literature.
Joint work with: Konstantinos Georgatzis, Chris Hawthorne, Partha Lal, Martin Shaw, Ian Piper.

Programme

6:30 Drinks and food

7:00 Introduction by QuantumBlack and talk by Professor Chris Williams

8:00 Questions + some more drinks

9:00-9:30 All done.

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Ian Morgan

Bayesian networks London

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Healthcare condition monitoring using ICU data

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Healthcare condition monitoring using ICU data

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