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Rob S MacLeod

Showing results (61-70 of 140) with videos related to

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Computing in Cardiology|May 3, 2021
Quantifying the Spatiotemporal Influence of Acute Myocardial Ischemia on Volumetric Conduction SpeedsWilson W Good, Brian Zenger, Jake A Bergquist, et al.
Computing in Cardiology|May 3, 2021
Effect of Myocardial Fiber Direction on Epicardial Activation PatternsLindsay C Rupp, Wilson W Good, Jake A Bergquist, et al.
Journal of Cardiovascular Electrophysiology|September 15, 2020
Reproducibility of clinical late gadolinium enhancement magnetic resonance imaging in detecting left atrial scar after atrial fibrillation ablationRoya Kamali, Joyce Schroeder, Edward DiBella, et al.
Medical & Biological Engineering & Computing|March 21, 2026
Uncertainty quantification of conduction velocity in models of cardiac spread of activationAnna Busatto, Lindsay C R Tanner, Jake A Bergquist, et al.
Clinical Medicine Insights. Cardiology|September 19, 2015
Computational Shape Models Characterize Shape Change of the Left Atrium in Atrial FibrillationJoshua Cates, Erik Bieging, Alan Morris, et al.
Journal of Cardiovascular Electrophysiology|January 10, 2020
Blanking period after radiofrequency ablation for atrial fibrillation guided by ablation lesion maturation based on serial MR imagingKennosuke Yamashita, Eugene Kwan, Roya Kamali, et al.
Computing in Cardiology|July 25, 2019
Novel Metric Using Laplacian Eigenmaps to Evaluate Ischemic Stress on the Torso SurfaceWilson W Good, Burak Erem, Jaume Coll-Font, et al.
Computing in Cardiology|April 28, 2022
A Cardiac Shape Model for Segmentation Uncertainty QuantificationJess D Tate, Shireen Elhabian, Nejib Zemzemi, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|November 16, 2007
Evaluation of different meshing algorithms in the computation of defibrillation thresholds in childrenJeroen G Stinstra, Matthew Jolley, Michael Callahan, et al.
Computing in Cardiology|October 6, 2025
Machine Learning Prediction of Blood Potassium at Different Time CutoffsJake A Bergquist, Deekshith Dade, Brian Zenger, et al.
Pageof 14

Showing results (61-70 of 140) with videos related to

Sort By:
Pageof 14
Computing in Cardiology|May 3, 2021
Quantifying the Spatiotemporal Influence of Acute Myocardial Ischemia on Volumetric Conduction SpeedsWilson W Good, Brian Zenger, Jake A Bergquist, et al.
Computing in Cardiology|May 3, 2021
Effect of Myocardial Fiber Direction on Epicardial Activation PatternsLindsay C Rupp, Wilson W Good, Jake A Bergquist, et al.
Journal of Cardiovascular Electrophysiology|September 15, 2020
Reproducibility of clinical late gadolinium enhancement magnetic resonance imaging in detecting left atrial scar after atrial fibrillation ablationRoya Kamali, Joyce Schroeder, Edward DiBella, et al.
Medical & Biological Engineering & Computing|March 21, 2026
Uncertainty quantification of conduction velocity in models of cardiac spread of activationAnna Busatto, Lindsay C R Tanner, Jake A Bergquist, et al.
Clinical Medicine Insights. Cardiology|September 19, 2015
Computational Shape Models Characterize Shape Change of the Left Atrium in Atrial FibrillationJoshua Cates, Erik Bieging, Alan Morris, et al.
Journal of Cardiovascular Electrophysiology|January 10, 2020
Blanking period after radiofrequency ablation for atrial fibrillation guided by ablation lesion maturation based on serial MR imagingKennosuke Yamashita, Eugene Kwan, Roya Kamali, et al.
Computing in Cardiology|July 25, 2019
Novel Metric Using Laplacian Eigenmaps to Evaluate Ischemic Stress on the Torso SurfaceWilson W Good, Burak Erem, Jaume Coll-Font, et al.
Computing in Cardiology|April 28, 2022
A Cardiac Shape Model for Segmentation Uncertainty QuantificationJess D Tate, Shireen Elhabian, Nejib Zemzemi, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|November 16, 2007
Evaluation of different meshing algorithms in the computation of defibrillation thresholds in childrenJeroen G Stinstra, Matthew Jolley, Michael Callahan, et al.
Computing in Cardiology|October 6, 2025
Machine Learning Prediction of Blood Potassium at Different Time CutoffsJake A Bergquist, Deekshith Dade, Brian Zenger, et al.
Pageof 14