Fast pre-clinical in-silico surrogate methods for statistical shape modelling

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Description/Abstract

In both industrial and clinical use, contemporary pre-clinical analysis methods place increasing emphasis on a more ‘holistic’ understanding of performance, accounting for a wider range of factors. This places a heavy time-burden on pre-clinical analysis methods, with wide-ranging stochastic methods, sweep studies or sensitivity analysis methods requiring extended processing time. In tension with this, there is an expectation that, in order to be practically useful, any computational support tool should be responsive, delivering results more quickly or even near-instantaneously for ‘real-time’ clinical use. The broad challenge is to make these models fast, accessible and relevant for end-users in a clinical and/or industrial context