Input-Output Non-Linear Dynamical Systems applied to Physiological Condition Monitoring

Konstantinos Georgatzis; Chris Williams; Christopher Hawthorne

Input-Output Non-Linear Dynamical Systems applied to Physiological Condition Monitoring

Konstantinos Georgatzis, Chris Williams, Christopher Hawthorne ;

Proceedings of the 1st Machine Learning for Healthcare Conference, PMLR 56:1-16, 2016.

Abstract

We 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 we are interested in modelling the effect of a widely used anaesthetic drug (Propofol) on a patient’s monitored depth of anaesthesia and haemodynamics. We compare our approach with one from the Pharmacokinetics/Pharmacodynamics (PK/PD) literature and show that we can provide significant improvements in performance without requiring the incorporation of expert physiological knowledge in our system.

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@InProceedings{pmlr-v56-Georgatzis16, title = {Input-Output Non-Linear Dynamical Systems applied to Physiological Condition Monitoring}, author = {Konstantinos Georgatzis and Chris Williams and Christopher Hawthorne}, booktitle = {Proceedings of the 1st Machine Learning for Healthcare Conference}, pages = {1--16}, year = {2016}, editor = {Finale Doshi-Velez and Jim Fackler and David Kale and Byron Wallace and Jenna Weins}, volume = {56}, series = {Proceedings of Machine Learning Research}, address = {Northeastern University, Boston, MA, USA}, month = {18--19 Aug}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v56/Georgatzis16.pdf}, url = {http://proceedings.mlr.press/v56/Georgatzis16.html}, abstract = {We 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 we are interested in modelling the effect of a widely used anaesthetic drug (Propofol) on a patient’s monitored depth of anaesthesia and haemodynamics. We compare our approach with one from the Pharmacokinetics/Pharmacodynamics (PK/PD) literature and show that we can provide significant improvements in performance without requiring the incorporation of expert physiological knowledge in our system.} }

%0 Conference Paper %T Input-Output Non-Linear Dynamical Systems applied to Physiological Condition Monitoring %A Konstantinos Georgatzis %A Chris Williams %A Christopher Hawthorne %B Proceedings of the 1st Machine Learning for Healthcare Conference %C Proceedings of Machine Learning Research %D 2016 %E Finale Doshi-Velez %E Jim Fackler %E David Kale %E Byron Wallace %E Jenna Weins %F pmlr-v56-Georgatzis16 %I PMLR %J Proceedings of Machine Learning Research %P 1--16 %U http://proceedings.mlr.press %V 56 %W PMLR %X We 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 we are interested in modelling the effect of a widely used anaesthetic drug (Propofol) on a patient’s monitored depth of anaesthesia and haemodynamics. We compare our approach with one from the Pharmacokinetics/Pharmacodynamics (PK/PD) literature and show that we can provide significant improvements in performance without requiring the incorporation of expert physiological knowledge in our system.

TY - CPAPER TI - Input-Output Non-Linear Dynamical Systems applied to Physiological Condition Monitoring AU - Konstantinos Georgatzis AU - Chris Williams AU - Christopher Hawthorne BT - Proceedings of the 1st Machine Learning for Healthcare Conference PY - 2016/12/10 DA - 2016/12/10 ED - Finale Doshi-Velez ED - Jim Fackler ED - David Kale ED - Byron Wallace ED - Jenna Weins ID - pmlr-v56-Georgatzis16 PB - PMLR SP - 1 DP - PMLR EP - 16 L1 - http://proceedings.mlr.press/v56/Georgatzis16.pdf UR - http://proceedings.mlr.press/v56/Georgatzis16.html AB - We 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 we are interested in modelling the effect of a widely used anaesthetic drug (Propofol) on a patient’s monitored depth of anaesthesia and haemodynamics. We compare our approach with one from the Pharmacokinetics/Pharmacodynamics (PK/PD) literature and show that we can provide significant improvements in performance without requiring the incorporation of expert physiological knowledge in our system. ER -

Georgatzis, K., Williams, C. & Hawthorne, C.. (2016). Input-Output Non-Linear Dynamical Systems applied to Physiological Condition Monitoring. Proceedings of the 1st Machine Learning for Healthcare Conference, in PMLR 56:1-16