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ORCIDRichard H. Clayton
Person information
- affiliation: University of Sheffield, Department of Computer Science, UK
- affiliation: Insigneo Institute for in-silico Medicine, Sheffield, UK
- affiliation (former): University of Leeds, School of Biomedical Sciences, UK
- affiliation (PhD): University in Newcastle upon Tyne, UK
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2020 – today
- 2023
[j17]Michail Mamalakis
, Pankaj Garg, Tom Nelson, Justin Lee, Andrew J. Swift, James M. Wild, Richard H. Clayton:
Artificial Intelligence framework with traditional computer vision and deep learning approaches for optimal automatic segmentation of left ventricle with scar. Artif. Intell. Medicine 143: 102610 (2023)- [j16]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:
Quantifying the impact of shape uncertainty on predicted arrhythmias. Comput. Biol. Medicine 153: 106528 (2023) - [j15]Michail Mamalakis, Pankaj Garg, Tom Nelson, Justin Lee, Andrew J. Swift, Jim M. Wild, Richard H. Clayton:
Automatic development of 3D anatomical models of border zone and core scar regions in the left ventricle. Comput. Medical Imaging Graph. 103: 102152 (2023) - 2022
- [c15]Sam Coveney, Cesare Corrado, Caroline H. Roney, Richard D. Wilkinson, Jeremy E. Oakley, Steven A. Niederer, Richard H. Clayton:
A Workflow for Probabilistic Calibration of Models of Left Atrial Electrophysiology. CinC 2022: 1-4 - 2021
- [j14]Michail Mamalakis, Pankaj Garg, Tom Nelson, Justin Lee, Jim M. Wild, Richard H. Clayton:
MA-SOCRATIS: An automatic pipeline for robust segmentation of the left ventricle and scar. Comput. Medical Imaging Graph. 93: 101982 (2021) - [j13]Michail Mamalakis, Andrew J. Swift, Bart Vorselaars, Surajit Ray, Simonne Weeks, Weiping Ding, Richard H. Clayton, Louise S. Mackenzie, Abhirup Banerjee:
DenResCov-19: A deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays. Comput. Medical Imaging Graph. 94: 102008 (2021) - [i2]Michail Mamalakis, Andrew J. Swift, Bart Vorselaars, Surajit Ray, Simonne Weeks, Weiping Ding, Richard H. Clayton, Louise S. Mackenzie, Abhirup Banerjee:
DenResCov-19: A deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays. CoRR abs/2104.04006 (2021) - 2020
- [j12]Cesare Corrado, Orod Razeghi, Caroline H. Roney, Sam Coveney, Steven Williams, Iain Sim, Mark D. O'Neill, Richard Wilkinson, Jeremy E. Oakley, Richard H. Clayton, Steven A. Niederer:
Quantifying atrial anatomy uncertainty from clinical data and its impact on electro-physiology simulation predictions. Medical Image Anal. 61: 101626 (2020) - [j11]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:
Probabilistic Interpolation of Uncertain Local Activation Times on Human Atrial Manifolds. IEEE Trans. Biomed. Eng. 67(1): 99-109 (2020) - [i1]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:
Gaussian Process Manifold Interpolation for Probabilistic Atrial Activation Maps and Uncertain Conduction Velocity. CoRR abs/2004.10586 (2020)
2010 – 2019
- 2018
- [j10]Barbara M. Johnston, Sam Coveney, Eugene T. Y. Chang, Peter R. Johnston, Richard H. Clayton:
Quantifying the effect of uncertainty in input parameters in a simplified bidomain model of partial thickness ischaemia. Medical Biol. Eng. Comput. 56(5): 761-780 (2018) - [c14]Cesare Corrado, Steven Williams, Iain Sim, Sam Coveney, Mark D. O'Neill, Richard Wilkinson, Jeremy E. Oakley, Richard H. Clayton, Steven A. Niederer:
An Algorithm to Sample an Anatomy With Uncertainty. CinC 2018: 1-4 - 2017
- [c13]Eugene T. Y. Chang, Sam Coveney, Richard H. Clayton:
Variance Based Sensitivity Analysis of I_Kr in a Model of the Human Atrial Action Potential Using Gaussian Process Emulators. FIMH 2017: 249-259 - 2015
- [c12]Julie Eatock, Yen Ting Lin, Eugene T. Y. Chang, Tobias Galla, Richard H. Clayton:
Assessing Measures of Atrial Fibrillation Clustering via Stochastic Models of Episode Recurrence and Disease Progression. CinC 2015: 265-268 - [c11]Eugene T. Y. Chang, Richard H. Clayton:
Parameter Sensitivity from Single Atrial Cell to Tissue: How Much does it Matter? A Simulation and Multivariate Regression Study. CinC 2015: 441-444 - [c10]Eugene T. Y. Chang, Richard H. Clayton:
Uncertainty and Sensitivity Analysis of the Courtemanche-Ramirez-Nattel Human Atrial Cell Model using Gaussian Process Emulators. CinC 2015: 857-860 - 2014
- [j9]Ivan V. Kazbanov, Richard H. Clayton, Martyn P. Nash, Chris P. Bradley, David J. Paterson, Martin P. Hayward, Peter Taggart, Alexander V. Panfilov:
Effect of Global Cardiac Ischemia on Human Ventricular Fibrillation: Insights from a Multi-scale Mechanistic Model of the Human Heart. PLoS Comput. Biol. 10(11) (2014) - [c9]Mitra Abbasi, Richard H. Clayton:
Formulation of ATP Sensitive K+ Current and Action Potential Shape in Models of Human Ventricular Myocytes. CinC 2014: 201-204 - [c8]Eugene T. Y. Chang, Richard H. Clayton:
Parameter Sensitivity Analysis of a Human Atrial Cell Model using Multivariate Regression. CinC 2014: 521-524 - [c7]Sathyavani Malyala, Richard H. Clayton:
The Effect of Scar Tissue on Complexity of Activation Patterns in Simulated Human Ventricular Fibrillation. CinC 2014: 1133-1136 - 2013
- [c6]Mitra Abbasi, Richard H. Clayton:
A Comparison of Two Models of Human Ventricular Tissue: Simulated Ischaemia and Re-entry. CinC 2013: 385-388 - [c5]Sathyavani Malyala, Richard H. Clayton:
Clustering of Re-entry Close to Scar Boundaries in Ventricular Tissue during Simulated Ventricular Fibrillation. CinC 2013: 1131-1134 - [c4]Richard H. Clayton:
Models of ventricular arrhythmia mechanisms. EMBC 2013: 1526-1529
2000 – 2009
- 2009
- [j8]Simon Scarle, Richard H. Clayton:
Early afterdepolarisations and ventricular arrhythmias in cardiac tissue: a computational study. Medical Biol. Eng. Comput. 47(3): 291-300 (2009) - 2006
- [c3]James W. Handley, Ken W. Brodlie, Richard H. Clayton:
Multi-Variate Visualization of Cardiac Virtual Tissue. CBMS 2006: 665-672 - 2005
- [c2]Ekaterina Zhuchkova, Richard H. Clayton:
Methods for Identifying and Tracking Phase Singularities in Computational Models of Re-entrant Fibrillation. FIMH 2005: 246-255 - 2004
- [j7]Richard H. Clayton, Arun V. Holden:
Filament behavior in a computational model of ventricular fibrillation in the canine heart. IEEE Trans. Biomed. Eng. 51(1): 28-34 (2004) - 2003
- [j6]Richard H. Clayton, Arun V. Holden:
Editorial. Int. J. Bifurc. Chaos 13(12): 3531-3534 (2003) - [j5]Min Chen, John V. Tucker, Richard H. Clayton, Arun V. Holden:
Constructive Volume Geometry Applied to Visualization of Cardiac Anatomy and Electrophysiology. Int. J. Bifurc. Chaos 13(12): 3591-3604 (2003) - [j4]Richard H. Clayton, Arun V. Holden:
Dynamics and Interaction of Filaments during reentry and Fibrillation in mammalian Virtual Ventricular Tissue. Int. J. Bifurc. Chaos 13(12): 3733-3745 (2003) - [j3]Richard H. Clayton, Arun V. Holden, W. C. Tong:
Can Endogenous, Noise-Triggered Early after-Depolarizations Initiate reentry in a Modified Luo-rudy Ventricular Virtual Tissue? Int. J. Bifurc. Chaos 13(12): 3835-3843 (2003) - [j2]Oleg V. Aslanidi, Richard H. Clayton, Arun V. Holden, H. K. Phillips, R. J. Ward:
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. Int. J. Bifurc. Chaos 13(12): 3865-3871 (2003) - [c1]Min Chen, Richard H. Clayton, Arun V. Holden, John V. Tucker:
Visualising Cardiac Anatomy Using Constructive Volume Geometry. FIMH 2003: 30-38 - 2001
- [j1]Michael Small, Dejin Yu, Robert G. Harrison, Richard H. Clayton, Trygve Eftestøl, Kjetil Sunde, Petter Andreas Steen:
Temporal Evolution of nonlinear Dynamics in Ventricular Arrhythmia. Int. J. Bifurc. Chaos 11(10): 2531-2548 (2001)
Coauthor Index
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