2023

Rabbani, A., Gao, H. , Lazarus, A., Dalton, D., Ge, Y., Mangion, K., Berry, C. and Husmeier, D. (2023) Image-based estimation of the left ventricular cavity volume using deep learning and Gaussian process with cardio-mechanical applications. Computerized Medical Imaging and Graphics, 106, 102203. (doi: 10.1016/j.compmedimag.2023.102203) (PMID:36848766)

2022

Lazarus, A., Gao, H. , Luo, X. and Husmeier, D. (2022) Improving cardio-mechanic inference by combining in vivo strain data with ex vivo volume–pressure data. Journal of the Royal Statistical Society: Series C (Applied Statistics), 71(4), pp. 906-931. (doi: 10.1111/rssc.12560)

Husmeier, D. , Dalton, D., Lazarus, A. and Gao, H. (2022) Forward and Inverse Uncertainty Quantification in Cardiac Mechanics. 4th International Conference on Statistics: Theory and Applications (ICSTA 22), Prague, Czech Republic, 28-30 July 2022. (doi: 10.11159/icsta22.161)

Lazarus, A., Dalton, D., Husmeier, D. and Gao, H. (2022) Sensitivity analysis and inverse uncertainty quantification for the left ventricular passive mechanics. Biomechanics and Modeling in Mechanobiology, 21(3), pp. 953-982. (doi: 10.1007/s10237-022-01571-8) (PMID:35377030) (PMCID:PMC9132878)

Borowska, A. , Gao, H. , Lazarus, A. and Husmeier, D. (2022) Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle. International Journal for Numerical Methods in Biomedical Engineering, 38(5), e3593. (doi: 10.1002/cnm.3593) (PMID:35302293)

2021

Romaszko, L., Borowska, A. , Lazarus, A., Dalton, D., Berry, C. , Luo, X. , Husmeier, D. and Gao, H. (2021) Neural network-based left ventricle geometry prediction from CMR images with application in biomechanics. Artificial Intelligence In Medicine, 119, 102140. (doi: 10.1016/j.artmed.2021.102140)

Dalton, D., Lazarus, A., Rabbani, A., Gao, H. and Husmeier, D. (2021) Graph Neural Network Emulation of Cardiac Mechanics. In: 3rd International Conference on Statistics: Theory and Applications (ICSTA'21), 29-31 Jul 2021, p. 127. ISBN 9781927877913 (doi: 10.11159/icsta21.127)

2020

Dalton, D., Lazarus, A. and Husmeier, D. (2020) Comparative evaluation of different emulators for cardiac mechanics. In: Ladde, G. and Noelle, S. (eds.) Proceedings of the 2nd International Conference on Statistics: Theory and Applications (ICSTA'20). Avestia Publishing: Ottawa, Canada, p. 126. ISBN 9781927877685 (doi: 10.11159/icsta20.126)

Li, W. et al. (2020) Analysis of cardiac amyloidosis progression using model-based markers. Frontiers in Physiology, 11, 324. (doi: 10.3389/fphys.2020.00324) (PMID:32425806) (PMCID:PMC7203577)

2019

Davies, V. , Noè, U. , Lazarus, A., Gao, H. , Macdonald, B. , Berry, C. , Luo, X. and Husmeier, D. (2019) Fast parameter inference in a biomechanical model of the left ventricle by using statistical emulation. Journal of the Royal Statistical Society: Series C (Applied Statistics), 68(5), pp. 1555-1576. (doi: 10.1111/rssc.12374) (PMID:31762497) (PMCID:PMC6856984)

Husmeier, D. , Lazarus, A., Noè, U. , Davies, V. , Borowska, A. , Macdonald, B. , Gao, H. , Berry, C. and Luo, X. (2019) Statistical Emulation of Cardiac Mechanics: an Important Step Towards a Clinical Decision Support System. In: International Conference on Statistics: Theory and Applications (ICSTA’19), Lisbon, Portugal, 13-14 Aug 2019, p. 29. ISBN 9781927877647 (doi: 10.11159/icsta19.29)

Romaszko, L., Borowska, A. , Lazarus, A., Gao, H. , Luo, X. and Husmeier, D. (2019) Direct Learning Left Ventricular Meshes from CMR Images. In: International Conference on Statistics: Theory and Applications (ICSTA’19), Lisbon, Portugal, 13-14 Aug 2019, p. 25. ISBN 9781927877647 (doi: 10.11159/icsta19.25)

Romaszko, L., Lazarus, A., Gao, H. , Borowska, A. , Luo, X. and Husmeier, D. (2019) Massive Dimensionality Reduction for the Left Ventricular Mesh. In: International Conference on Statistics: Theory and Applications (ICSTA’19), Lisbon, Portugal, 13-14 Aug 2019, p. 24. ISBN 9781927877647 (doi: 10.11159/icsta19.24)

Noè, U. , Lazarus, A., Gao, H. , Davies, V. , Macdonald, B. , Mangion, K., Berry, C. , Luo, X. and Husmeier, D. (2019) Gaussian process emulation to accelerate parameter estimation in a mechanical model of the left ventricle: a critical step towards clinical end-user relevance. Journal of the Royal Society: Interface, 16(156), 20190114. (doi: 10.1098/rsif.2019.0114) (PMID:31266415) (PMCID:PMC6685034)

2018

Lazarus, A., Husmeier, D. and Papamarkou, T. (2018) Multiphase MCMC sampling for parameter inference in nonlinear ordinary differential equations. Proceedings of Machine Learning Research, 84, pp. 1252-1260.

2017

Lazarus, A., Husmeier, D. and Papamarkou, T. (2017) Inference in Complex Systems Using Multi-Phase MCMC Sampling with Gradient Matching. RSS 2017 Annual Conference, Glasgow, Scotland, 04-07 Sep 2017.

Lazarus, A., Husmeier, D. and Papamarkou, T. (2017) Inference in Complex Systems Using Multi-Phase MCMC Sampling With Gradient Matching Burn-in. In: 32nd International Workshop on Statistical Modelling, Groningen, Netherlands, 03-07 Jul 2017, pp. 52-57.

Articles

Rabbani, A., Gao, H. , Lazarus, A., Dalton, D., Ge, Y., Mangion, K., Berry, C. and Husmeier, D. (2023) Image-based estimation of the left ventricular cavity volume using deep learning and Gaussian process with cardio-mechanical applications. Computerized Medical Imaging and Graphics, 106, 102203. (doi: 10.1016/j.compmedimag.2023.102203) (PMID:36848766)

Lazarus, A., Gao, H. , Luo, X. and Husmeier, D. (2022) Improving cardio-mechanic inference by combining in vivo strain data with ex vivo volume–pressure data. Journal of the Royal Statistical Society: Series C (Applied Statistics), 71(4), pp. 906-931. (doi: 10.1111/rssc.12560)

Lazarus, A., Dalton, D., Husmeier, D. and Gao, H. (2022) Sensitivity analysis and inverse uncertainty quantification for the left ventricular passive mechanics. Biomechanics and Modeling in Mechanobiology, 21(3), pp. 953-982. (doi: 10.1007/s10237-022-01571-8) (PMID:35377030) (PMCID:PMC9132878)

Borowska, A. , Gao, H. , Lazarus, A. and Husmeier, D. (2022) Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle. International Journal for Numerical Methods in Biomedical Engineering, 38(5), e3593. (doi: 10.1002/cnm.3593) (PMID:35302293)

Romaszko, L., Borowska, A. , Lazarus, A., Dalton, D., Berry, C. , Luo, X. , Husmeier, D. and Gao, H. (2021) Neural network-based left ventricle geometry prediction from CMR images with application in biomechanics. Artificial Intelligence In Medicine, 119, 102140. (doi: 10.1016/j.artmed.2021.102140)

Li, W. et al. (2020) Analysis of cardiac amyloidosis progression using model-based markers. Frontiers in Physiology, 11, 324. (doi: 10.3389/fphys.2020.00324) (PMID:32425806) (PMCID:PMC7203577)

Davies, V. , Noè, U. , Lazarus, A., Gao, H. , Macdonald, B. , Berry, C. , Luo, X. and Husmeier, D. (2019) Fast parameter inference in a biomechanical model of the left ventricle by using statistical emulation. Journal of the Royal Statistical Society: Series C (Applied Statistics), 68(5), pp. 1555-1576. (doi: 10.1111/rssc.12374) (PMID:31762497) (PMCID:PMC6856984)

Noè, U. , Lazarus, A., Gao, H. , Davies, V. , Macdonald, B. , Mangion, K., Berry, C. , Luo, X. and Husmeier, D. (2019) Gaussian process emulation to accelerate parameter estimation in a mechanical model of the left ventricle: a critical step towards clinical end-user relevance. Journal of the Royal Society: Interface, 16(156), 20190114. (doi: 10.1098/rsif.2019.0114) (PMID:31266415) (PMCID:PMC6685034)

Lazarus, A., Husmeier, D. and Papamarkou, T. (2018) Multiphase MCMC sampling for parameter inference in nonlinear ordinary differential equations. Proceedings of Machine Learning Research, 84, pp. 1252-1260.

Book Sections

Dalton, D., Lazarus, A. and Husmeier, D. (2020) Comparative evaluation of different emulators for cardiac mechanics. In: Ladde, G. and Noelle, S. (eds.) Proceedings of the 2nd International Conference on Statistics: Theory and Applications (ICSTA'20). Avestia Publishing: Ottawa, Canada, p. 126. ISBN 9781927877685 (doi: 10.11159/icsta20.126)

Conference or Workshop Item

Husmeier, D. , Dalton, D., Lazarus, A. and Gao, H. (2022) Forward and Inverse Uncertainty Quantification in Cardiac Mechanics. 4th International Conference on Statistics: Theory and Applications (ICSTA 22), Prague, Czech Republic, 28-30 July 2022. (doi: 10.11159/icsta22.161)

Lazarus, A., Husmeier, D. and Papamarkou, T. (2017) Inference in Complex Systems Using Multi-Phase MCMC Sampling with Gradient Matching. RSS 2017 Annual Conference, Glasgow, Scotland, 04-07 Sep 2017.

Conference Proceedings

Dalton, D., Lazarus, A., Rabbani, A., Gao, H. and Husmeier, D. (2021) Graph Neural Network Emulation of Cardiac Mechanics. In: 3rd International Conference on Statistics: Theory and Applications (ICSTA'21), 29-31 Jul 2021, p. 127. ISBN 9781927877913 (doi: 10.11159/icsta21.127)

Husmeier, D. , Lazarus, A., Noè, U. , Davies, V. , Borowska, A. , Macdonald, B. , Gao, H. , Berry, C. and Luo, X. (2019) Statistical Emulation of Cardiac Mechanics: an Important Step Towards a Clinical Decision Support System. In: International Conference on Statistics: Theory and Applications (ICSTA’19), Lisbon, Portugal, 13-14 Aug 2019, p. 29. ISBN 9781927877647 (doi: 10.11159/icsta19.29)

Romaszko, L., Borowska, A. , Lazarus, A., Gao, H. , Luo, X. and Husmeier, D. (2019) Direct Learning Left Ventricular Meshes from CMR Images. In: International Conference on Statistics: Theory and Applications (ICSTA’19), Lisbon, Portugal, 13-14 Aug 2019, p. 25. ISBN 9781927877647 (doi: 10.11159/icsta19.25)

Romaszko, L., Lazarus, A., Gao, H. , Borowska, A. , Luo, X. and Husmeier, D. (2019) Massive Dimensionality Reduction for the Left Ventricular Mesh. In: International Conference on Statistics: Theory and Applications (ICSTA’19), Lisbon, Portugal, 13-14 Aug 2019, p. 24. ISBN 9781927877647 (doi: 10.11159/icsta19.24)

Lazarus, A., Husmeier, D. and Papamarkou, T. (2017) Inference in Complex Systems Using Multi-Phase MCMC Sampling With Gradient Matching Burn-in. In: 32nd International Workshop on Statistical Modelling, Groningen, Netherlands, 03-07 Jul 2017, pp. 52-57.