Deep Learning Over Reduced Intrinsic Domains for Efficient Mechanics of the Left Ventricle

Comprehensive Uncertainty Quantification and Sensitivity Analysis for Cardiac Action Potential Models

(2019) Pras Pathmanathan et al.   Frontiers in Physiology

A Survey of Flattening-Based Medical Visualization Techniques

(2018) J. Kreiser et al.   COMPUTER GRAPHICS FORUM

A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis

(2018) Liang Liang et al.   Journal of the Royal Society Interface

Left Ventricular Diastolic Myocardial Stiffness and End-Diastolic Myofibre Stress in Human Heart Failure Using Personalised Biomechanical Analysis

(2018) Zhinuo J. Wang et al.   Journal of Cardiovascular Translational Research

Projection-based model reduction: Formulations for physics-based machine learning

(2018) Renee Swischuk et al.   COMPUTERS & FLUIDS

DGM: A deep learning algorithm for solving partial differential equations

(2018) Justin Sirignano et al.   JOURNAL OF COMPUTATIONAL PHYSICS

A unified deep artificial neural network approach to partial differential equations in complex geometries

(2018) Jens Berg et al.   NEUROCOMPUTING

Computational models in cardiology

(2018) Steven A. Niederer et al.   Nature Reviews Cardiology

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

(2018) M. Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Machine learning of linear differential equations using Gaussian processes

(2017) Maziar Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Using physiologically based models for clinical translation: predictive modelling, data interpretation or something in-between?

(2016) Steven A. Niederer et al.   JOURNAL OF PHYSIOLOGY-LONDON

Multiphysics and multiscale modelling, data–model fusion and integration of organ physiology in the clinic: ventricular cardiac mechanics

(2016) Radomir Chabiniok et al.   Interface Focus

Image-Based Predictive Modeling of Heart Mechanics

(2015) V.Y. Wang et al.   Annual Review of Biomedical Engineering

Computational fluid dynamics modelling in cardiovascular medicine

(2015) Paul D Morris et al.   HEART

A constrained integration (CINT) approach to solving partial differential equations using artificial neural networks

(2015) Keith Rudd et al.   NEUROCOMPUTING

OpenCMISS: A multi-physics & multi-scale computational infrastructure for the VPH/Physiome project

(2011) Chris Bradley et al.   PROGRESS IN BIOPHYSICS & MOLECULAR BIOLOGY

Artificial Neural Network Method for Solution of Boundary Value Problems With Exact Satisfaction of Arbitrary Boundary Conditions

(2009) K.S. McFall et al.   IEEE TRANSACTIONS ON NEURAL NETWORKS

Modelling passive diastolic mechanics with quantitative MRI of cardiac structure and function

(2009) Vicky Y. Wang et al.   MEDICAL IMAGE ANALYSIS