University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > Learning between digital twins

Learning between digital twins

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact info@newton.ac.uk.

FHTW01 - Uncertainty quantification for cardiac models

This work is motivated by, and is part of, a project that aim to develop digital twins for essential hypertension management and treatment through physically based computer models,  new sensor data and traditional population based data. Our approach is that the individual digital twins should learn from each other. We explore doing this by combining Bayesian model calibration and mixed models for simplified models. This is work in progress.

This talk is part of the Isaac Newton Institute Seminar Series series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2019 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity