The use of numerical modelling and mathematical analysis in healthcare and medicine is increasing and is starting to be used to guide treatments. However, we know that our models and techniques are not perfect, and for application we need to know the effect of imperfections on our results. For example, our models contain unknown parameters, initial and boundary conditions, and even the model structure is uncertain. Uncertainty quantification is a set of mathematical and statistical techniques that enable us to estimate these uncertainties and to reduce them by calibration with data (inverse modelling). In this workshop, co hosted by the CMIH, and the Centre for Predictive Modelling in Healthcare, we will explore the use of such methods in the context of the new EPSRC Centres for Mathematical Sciences in Healthcare and consider their implications for patients and new interventions. We will examine the different approaches being used across the Centres and discuss how progress might be made. The workshop will be of interest to those working in the Centres and to others working in related areas who may be interested in collaboration, or simply in knowing more about uncertainty quantification in the mathematics of healthcare.
The Programme is as follows:
10:50 Welcome – Professor Peter Challenor (Centre for Predictive Modelling in Healthcare, Exeter)
11:00 Strategy and Vision for the EPSRC Centres for Mathematical Sciences in Healthcare and further opportunities – Mark Tarplee (Healthcare Technologies Manager, EPSRC)
11:30 Uncertainties and variability in cardiac modelling – Dr Gary Mirams (University of Nottingham)
12:15 Joining Uncertainty Quantification across applied mathematics and statistics – Professor John Aston and Dr Carola Schönlieb (Centre for Mathematical Imaging in Healthcare, University of Cambridge)
13:45 Calibration of models with patient data – Professor Peter Challenor (Centre for Predictive Modelling in Healthcare, University of Exeter)
14:15 Communicating risk and uncertainty to patients – Professor Sir David Spiegelhalter (Winton Centre, University of Cambridge)
15:00 The use of credible intervals in longitudinal discriminant analysis to improve clinical classification – Dr Marta Garcia-Finana (Centre for Mathematics in Healthcare, University of Liverpool)
15:15 Insights on the Structure of the MAP Kinase Signalling Pathway by Quantified Uncertainty – Professor Mark Girolami (Centre for Mathematics of Precision Healthcare, Imperial College London)
15:30 Tea/coffee break
16:00 Discussion – the way ahead
16:45 Summary & next steps
Registration for this event is now closed.