Temporal Evolution of nonlinear Dynamics in Ventricular Arrhythmia. - Michael Small; Dejin Yu; Robert G. Harrison; Richard H. Clayton; Trygve Eftestøl; Kjetil Sunde; Petter Andreas Steen (Int. J. Bifurc. Chaos, 2001)

Visualising Cardiac Anatomy Using Constructive Volume Geometry. - Min Chen 001; Richard H. Clayton; Arun V. Holden; John V. Tucker (FIMH, 2003)

Vulnerability to reentry, and Drift, Stability and breakdown of Spiral Waves in a Linear Gradient of Gk in a Luo-rudy 1 Virtual Ventricular Tissue. - Oleg V. Aslanidi; Richard H. Clayton; Arun V. Holden; H. K. Phillips; R. J. Ward (Int. J. Bifurc. Chaos, 2003)

Constructive Volume Geometry Applied to Visualization of Cardiac Anatomy and Electrophysiology. - Min Chen 001; John V. Tucker; Richard H. Clayton; Arun V. Holden (Int. J. Bifurc. Chaos, 2003)

Editorial. - Richard H. Clayton; Arun V. Holden (Int. J. Bifurc. Chaos, 2003)

Dynamics and Interaction of Filaments during reentry and Fibrillation in mammalian Virtual Ventricular Tissue. - Richard H. Clayton; Arun V. Holden (Int. J. Bifurc. Chaos, 2003)

Can Endogenous, Noise-Triggered Early after-Depolarizations Initiate reentry in a Modified Luo-rudy Ventricular Virtual Tissue? - Richard H. Clayton; Arun V. Holden; W. C. Tong (Int. J. Bifurc. Chaos, 2003)

Filament behavior in a computational model of ventricular fibrillation in the canine heart. - Richard H. Clayton; Arun V. Holden (IEEE Trans. Biomed. Eng., 2004)

Methods for Identifying and Tracking Phase Singularities in Computational Models of Re-entrant Fibrillation. - Ekaterina Zhuchkova; Richard H. Clayton (FIMH, 2005)

Multi-Variate Visualization of Cardiac Virtual Tissue. - James W. Handley; Ken W. Brodlie; Richard H. Clayton (CBMS, 2006)

Early afterdepolarisations and ventricular arrhythmias in cardiac tissue: a computational study. - Simon Scarle; Richard H. Clayton (Medical Biol. Eng. Comput., 2009)

A Comparison of Two Models of Human Ventricular Tissue: Simulated Ischaemia and Re-entry. - Mitra Abbasi; Richard H. Clayton (CinC, 2013)

Clustering of Re-entry Close to Scar Boundaries in Ventricular Tissue during Simulated Ventricular Fibrillation. - Sathyavani Malyala; Richard H. Clayton (CinC, 2013)

Models of ventricular arrhythmia mechanisms. - Richard H. Clayton (EMBC, 2013)

Formulation of ATP Sensitive K+ Current and Action Potential Shape in Models of Human Ventricular Myocytes. - Mitra Abbasi; Richard H. Clayton (CinC, 2014)

Parameter Sensitivity Analysis of a Human Atrial Cell Model using Multivariate Regression. - Eugene T. Y. Chang; Richard H. Clayton (CinC, 2014)

The Effect of Scar Tissue on Complexity of Activation Patterns in Simulated Human Ventricular Fibrillation. - Sathyavani Malyala; Richard H. Clayton (CinC, 2014)

Effect of Global Cardiac Ischemia on Human Ventricular Fibrillation: Insights from a Multi-scale Mechanistic Model of the Human Heart. - Ivan V. Kazbanov; Richard H. Clayton; Martyn P. Nash; Chris P. Bradley; David J. Paterson; Martin P. Hayward; Peter Taggart; Alexander V. Panfilov (PLoS Comput. Biol., 2014)

Parameter Sensitivity from Single Atrial Cell to Tissue: How Much does it Matter? A Simulation and Multivariate Regression Study. - Eugene T. Y. Chang; Richard H. Clayton (CinC, 2015)

Uncertainty and Sensitivity Analysis of the Courtemanche-Ramirez-Nattel Human Atrial Cell Model using Gaussian Process Emulators. - Eugene T. Y. Chang; Richard H. Clayton (CinC, 2015)

Assessing Measures of Atrial Fibrillation Clustering via Stochastic Models of Episode Recurrence and Disease Progression. - Julie Eatock; Yen Ting Lin; Eugene T. Y. Chang; Tobias Galla; Richard H. Clayton (CinC, 2015)

Variance Based Sensitivity Analysis of I_Kr in a Model of the Human Atrial Action Potential Using Gaussian Process Emulators. - Eugene T. Y. Chang; Sam Coveney; Richard H. Clayton (FIMH, 2017)

An Algorithm to Sample an Anatomy With Uncertainty. - Cesare Corrado; Steven Williams 001; Iain Sim; Sam Coveney; Mark D. O'Neill; Richard Wilkinson; Jeremy E. Oakley; Richard H. Clayton; Steven A. Niederer (CinC, 2018)

Quantifying the effect of uncertainty in input parameters in a simplified bidomain model of partial thickness ischaemia. - Barbara M. Johnston; Sam Coveney; Eugene T. Y. Chang; Peter R. Johnston; Richard H. Clayton (Medical Biol. Eng. Comput., 2018)

Gaussian Process Manifold Interpolation for Probabilistic Atrial Activation Maps and Uncertain Conduction Velocity. - Sam Coveney; Cesare Corrado; Caroline H. Roney; Daniel O'Hare; Steven E. Williams; Mark D. O'Neill; Steven A. Niederer; Richard H. Clayton; Jeremy E. Oakley; Richard D. Wilkinson (CoRR, 2020)

Quantifying atrial anatomy uncertainty from clinical data and its impact on electro-physiology simulation predictions. - Cesare Corrado; Orod Razeghi; Caroline H. Roney; Sam Coveney; Steven Williams 001; Iain Sim; Mark D. O'Neill; Richard Wilkinson; Jeremy E. Oakley; Richard H. Clayton; Steven A. Niederer (Medical Image Anal., 2020)

Probabilistic Interpolation of Uncertain Local Activation Times on Human Atrial Manifolds. - Sam Coveney; Richard H. Clayton; Cesare Corrado; Caroline H. Roney; Richard Wilkinson; Jeremy E. Oakley; Finn Lindgren; Steven E. Williams; Mark D. O'Neill; Steven A. Niederer (IEEE Trans. Biomed. Eng., 2020)

MA-SOCRATIS: An automatic pipeline for robust segmentation of the left ventricle and scar. - Michail Mamalakis; Pankaj Garg; Tom Nelson; Justin Lee; Jim M. Wild; Richard H. Clayton (Comput. Medical Imaging Graph., 2021)

DenResCov-19: A deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays. - Michail Mamalakis; Andrew J. Swift; Bart Vorselaars; Surajit Ray; Simonne Weeks; Weiping Ding 001; Richard H. Clayton; Louise S. Mackenzie; Abhirup Banerjee (Comput. Medical Imaging Graph., 2021)

A Workflow for Probabilistic Calibration of Models of Left Atrial Electrophysiology. - Sam Coveney; Cesare Corrado; Caroline H. Roney; Richard D. Wilkinson; Jeremy E. Oakley; Steven A. Niederer; Richard H. Clayton (CinC, 2022)

Automatic development of 3D anatomical models of border zone and core scar regions in the left ventricle. - Michail Mamalakis; Pankaj Garg; Tom Nelson; Justin Lee; Andrew J. Swift; Jim M. Wild; Richard H. Clayton (Comput. Medical Imaging Graph., 2023)

Quantifying the impact of shape uncertainty on predicted arrhythmias. - Cesare Corrado; Caroline H. Roney; Orod Razeghi; José Alonso Solís-Lemus; Sam Coveney; Iain Sim; Steven E. Williams; Mark D. O'Neill; Richard D. Wilkinson; Richard H. Clayton; Steven A. Niederer (Comput. Biol. Medicine, 2023)

Artificial Intelligence framework with traditional computer vision and deep learning approaches for optimal automatic segmentation of left ventricle with scar. - Michail Mamalakis; Pankaj Garg; Tom Nelson; Justin Lee; Andrew J. Swift; James M. Wild; Richard H. Clayton (Artif. Intell. Medicine, 2023)

Convergence, sampling and total order estimator effects on parameter orthogonality in global sensitivity analysis. - Harry Saxton; Xu Xu 005; Torsten Schenkel; Richard H. Clayton; Ian Halliday (PLoS Comput. Biol., 2024)

Deep multi-metric training: the need of multi-metric curve evaluation to avoid weak learning. - Michail Mamalakis; Abhirup Banerjee; Surajit Ray; Craig Wilkie; Richard H. Clayton; Andrew J. Swift; George Panoutsos; Bart Vorselaars (Neural Comput. Appl., 2024)

CLAIM: Clinically-Guided LGE Augmentation for Realistic and Diverse Myocardial Scar Synthesis and Segmentation. - Farheen Ramzan; Yusuf Kiberu; Nikesh Jathanna; Shahnaz Jamil-Copley; Richard H. Clayton; Chen Chen (AIiH (1), 2025)