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Found 5 papers, 2 papers with code
Estimation of fibre architecture and scar in myocardial tissue using electrograms: an in-silico study
We adapt a wavelet-based surrogate testing analysis to confirm that the inferred conductivity distribution is an accurate representation of the ground truth input to the model.
Considering discrepancy when calibrating a mechanistic electrophysiology model
Uncertainty quantification (UQ) is a vital step in using mathematical models and simulations to take decisions.
Nektar++: enhancing the capability and application of high-fidelity spectral/$hp$ element methods
Nektar++ is an open-source framework that provides a flexible, high-performance and scalable platform for the development of solvers for partial differential equations using the high-order spectral/$hp$ element method.
Mathematical Software Numerical Analysis Numerical Analysis Fluid Dynamics
Approximating the solution to wave propagation using deep neural networks
In this work, we suggest a neural network capable of understanding a specific physical phenomenon: wave propagation in a two-dimensional medium.
Rethinking multiscale cardiac electrophysiology with machine learning and predictive modelling
We review some of the latest approaches to analysing cardiac electrophysiology data using machine learning and predictive modelling.
