Predictive Digital Twins with Quantified Uncertainty for Patient-Specific Decision Making in Oncology.

Validating the predictions of mathematical models describing tumor growth and treatment response.

a priori uncertainty quantification of reacting turbulence closure models using Bayesian neural networks.

Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas.