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Uncertainty aware training to improve deep learning model calibration for classification of cardiac MR images.

T. Dawood, C. Chen, B. Sidhu, B. Ruijsink, J. Gould, B. Porter, M. Elliott, V. Mehta, C. Rinaldi, E. Puyol-Antón, R. Razavi, and A. King. Medical Image Anal., (August 2023)

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Laura Porter

Bradley Miller

William Bradley

Bradley Heins

Bradley Lushman

Other publications of authors with the same name

A multimodal deep learning model for cardiac resynchronisation therapy response prediction.E. Puyol-Antón, B. Sidhu, J. Gould, B. Porter, M. Elliott, V. Mehta, C. Rinaldi, and A. King. Medical Image Anal., (2022)Uncertainty Aware Training to Improve Deep Learning Model Calibration for Classification of Cardiac MR Images.T. Dawood, C. Chen, B. Sidhua, B. Ruijsink, J. Gould, B. Porter, M. Elliott, V. Mehta, C. Rinaldi, E. Puyol-Antón and 2 other author(s). CoRR, (2023)Assessing the ability of substrate mapping techniques to guide ventricular tachycardia ablation using computational modelling.F. Campos, M. Orini, R. Arnold, J. Whitaker, M. O'Neill, R. Razavi, G. Plank, B. Hanson, B. Porter, C. Rinaldi and 4 other author(s). Comput. Biol. Medicine, (2021)The Effects of Non-ischemic Fibrosis Texture and Density on Mechanisms of Reentry.G. Balaban, C. Costa, B. Halliday, B. Porter, W. Bai, G. Plank, C. Rinaldi, D. Rueckert, S. Prasad, and M. Bishop. CinC, page 1-4. www.cinc.org, (2018)Uncertainty aware training to improve deep learning model calibration for classification of cardiac MR images.T. Dawood, C. Chen, B. Sidhu, B. Ruijsink, J. Gould, B. Porter, M. Elliott, V. Mehta, C. Rinaldi, E. Puyol-Antón and 2 other author(s). Medical Image Anal., (August 2023)Characterizing the clinical implementation of a novel activation-repolarization metric to identify targets for catheter ablation of ventricular tachycardias using computational models.F. Campos, M. Orini, P. Taggart, B. Hanson, P. Lambiase, B. Porter, C. Rinaldi, J. Gill, and M. Bishop. Comput. Biol. Medicine, (2019)Scar shape analysis and simulated electrical instabilities in a non-ischemic dilated cardiomyopathy patient cohort.G. Balaban, B. Halliday, W. Bai, B. Porter, C. Malvuccio, P. Lamata, C. Rinaldi, G. Plank, D. Rueckert, S. Prasad and 1 other author(s). PLoS Comput. Biol., (2019)Personalized Modelling Pipeline for Cardiac Electrophysiology Simulations of Cardiac Resynchronization Therapy in Infarct patients.C. Costa, A. Neic, G. Plank, E. Kerfoot, B. Porter, B. Sieniewicz, J. Gould, B. Sidhu, Z. Chen, C. Rinaldi and 2 other author(s). CinC, page 1-4. www.cinc.org, (2018)Uncertainty-Aware Training for Cardiac Resynchronisation Therapy Response Prediction.T. Dawood, C. Chen, R. Andlauer, B. Sidhu, B. Ruijsink, J. Gould, B. Porter, M. Elliott, V. Mehta, C. Rinaldi and 3 other author(s). STACOM@MICCAI, volume 13131 of Lecture Notes in Computer Science, page 189-198. Springer, (2021)Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction.E. Puyol-Antón, C. Chen, J. Clough, B. Ruijsink, B. Sidhu, J. Gould, B. Porter, M. Elliott, V. Mehta, D. Rueckert and 2 other author(s). MICCAI (1), volume 12261 of Lecture Notes in Computer Science, page 284-293. Springer, (2020)

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Disambiguation of "Porter, Bradley"

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Uncertainty aware training to improve deep learning model calibration for classification of cardiac MR images.

Please choose a person to relate this publication to

Laura Porter

Bradley Miller

William Bradley

Bradley Heins

Bradley Lushman

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Porter, Bradley"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Uncertainty aware training to improve deep learning model calibration for classification of cardiac MR images.

Please choose a person to relate this publication to

Laura Porter

Bradley Miller

William Bradley

Bradley Heins

Bradley Lushman

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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URL
DOI
BibTeX
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APA
Chicago
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Uncertainty aware training to improve deep learning model calibration for classification of cardiac MR images.