100 citations · 117 across the 4 of their papers we have counts for
4 papers
TumorTwin: A python framework for patient-specific digital twins in oncology
Michael Kapteyn, Anirban Chaudhuri, Ernesto A. B. F. Lima +5
Background: Advances in the theory and methods of computational oncology have enabled accurate characterization and prediction of tumor growth and treatment response on a patient-s…
Predictive Digital Twin for Optimizing Patient-Specific Radiotherapy Regimens under Uncertainty in High-Grade Gliomas
Anirban Chaudhuri, Graham Pash, David A. Hormuth +6
We develop a methodology to create data-driven predictive digital twins for optimal risk-aware clinical decision-making. We illustrate the methodology as an enabler for an anticipa…
A Probabilistic Graphical Model Foundation for Enabling Predictive Digital Twins at Scale
Michael G. Kapteyn, Jacob V. R. Pretorius, Karen E. Willcox
A unifying mathematical formulation is needed to move from one-off digital twins built through custom implementations to robust digital twin implementations at scale. This work pro…
From Physics-Based Models to Predictive Digital Twins via Interpretable Machine Learning
Michael G. Kapteyn, Karen E. Willcox
This work develops a methodology for creating a data-driven digital twin from a library of physics-based models representing various asset states. The digital twin is updated using…