Fast and robust parameter estimation with uncertainty quantification for the cardiac function.

Journal: Computer methods and programs in biomedicine
PMID:

Abstract

BACKGROUND AND OBJECTIVES: Parameter estimation and uncertainty quantification are crucial in computational cardiology, as they enable the construction of digital twins that faithfully replicate the behavior of physical patients. Many model parameters regarding cardiac electromechanics and cardiovascular hemodynamics need to be robustly fitted by starting from a few, possibly non-invasive, noisy observations. Moreover, short execution times and a small amount of computational resources are required for the effective clinical translation.

Authors

  • Matteo Salvador
    MOX-Dipartimento di Matematica, P.zza Leonardo da Vinci 32, Milan, 20133, Italy. Electronic address: matteo1.salvador@polimi.it.
  • Francesco Regazzoni
    MOX-Mathematics Department, Politecnico di Milano, Milano, Italy.
  • Luca Dede'
    MOX-Dipartimento di Matematica, P.zza Leonardo da Vinci 32, Milan, 20133, Italy.
  • Alfio Quarteroni
    MOX - Dipartimento di Matematica, Politecnico di Milano, Milano, Italy.