Forecasting personal health in an uncertain environment

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Quantifying uncertainty in multiscale models for biomedical applications, University of Sheffield Friday 21 April 2017

Approaches for uncertainty quantification

Jeremy Oakley – Gaussian process emulators

Lindsay Lee – Sensitivity analysis with a global model

Mark Strong – Managing model uncertainty in the absence of calibration data

Richard Wilkinson – Approximate Bayesian computation - likelihood-free inference for complex models

Biomedical applications

Michael Colman – From calcium sparks to fibrillation in the heart: modelling the arrhythmic consequences of the propagation of microscopic fluctuations to the macroscopic

Lingzhong Guo – Data-based modelling for estimation of bone adaptation pattern in mouse tibia

Eugene Chang – Uncertainty and sensitivity analysis for cardiac cell models

Alessandro Melis – Sensitivity analysis for cardiovascular modelling with Gaussian process emulators

Sam Coveney – GP_emu, a Python based environment for uncertainty and sensitivity analysis with Gaussian processes

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QUINTET is EPSRC grant EP/K037145/1
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