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A Bergquist

Showing results (41-50 of 120) with videos related to

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Computing in Cardiology|February 5, 2026
Predicting Ventricular Arrhythmia in Myocardial Ischemia Using Machine LearningAnna Busatto, Jake A Bergquist, Tolga Tasdizen, et al.
Computing in Cardiology|March 20, 2020
Experimental Validation of Image-Based Modeling of Torso Surface Potentials During Acute Myocardial IschemiaBrian Zenger, Jake A Bergquist, Wilson W Good, et al.
Computers in Biology and Medicine|May 29, 2021
The electrocardiographic forward problem: A benchmark studyJake A Bergquist, Wilson W Good, Brian Zenger, et al.
Computing in Cardiology|May 3, 2021
Novel Experimental Preparation to Assess Electrocardiographic Imaging Reconstruction TechniquesJake A Bergquist, Brian Zenger, Wilson W Good, et al.
Computing in Cardiology|October 6, 2025
A Survey of Augmentation Techniques for Enhancing ECG Representation Through Self-Supervised Contrastive LearningDeekshith Dade, Jake A Bergquist, Rob S MacLeod, et al.
Fertility and Sterility|July 1, 1996
Immediate postpartum insertion of the norplant contraceptive deviceJ R Molland, D B Morehead, D M Baldwin, et al.
Obstetrics and Gynecology|August 1, 1982
Artificial insemination with fresh donor semen using the cervical cap technique: a review of 278 casesC A Bergquist, J A Rock, J Miller, et al.
Computing in Cardiology|April 25, 2022
Myocardial Ischemia Detection Using Body Surface Potential Mappings and Machine LearningJames N Brundage, Vai Suliafu, Jake A Bergquist, et al.
Computing in Cardiology|August 28, 2024
Uncertainty Quantification of Fiber Orientation and Epicardial ActivationLindsay C Rupp, Anna Busatto, Jake A Bergquist, et al.
Frontiers in Physiology|June 5, 2023
Investigation into the importance of using natural PVCs and pathological models for potential-based ECGI validationLaura R Bear, Jake A Bergquist, Emma Abell, et al.
Pageof 12

Showing results (41-50 of 120) with videos related to

Sort By:
Pageof 12
Computing in Cardiology|February 5, 2026
Predicting Ventricular Arrhythmia in Myocardial Ischemia Using Machine LearningAnna Busatto, Jake A Bergquist, Tolga Tasdizen, et al.
Computing in Cardiology|March 20, 2020
Experimental Validation of Image-Based Modeling of Torso Surface Potentials During Acute Myocardial IschemiaBrian Zenger, Jake A Bergquist, Wilson W Good, et al.
Computers in Biology and Medicine|May 29, 2021
The electrocardiographic forward problem: A benchmark studyJake A Bergquist, Wilson W Good, Brian Zenger, et al.
Computing in Cardiology|May 3, 2021
Novel Experimental Preparation to Assess Electrocardiographic Imaging Reconstruction TechniquesJake A Bergquist, Brian Zenger, Wilson W Good, et al.
Computing in Cardiology|October 6, 2025
A Survey of Augmentation Techniques for Enhancing ECG Representation Through Self-Supervised Contrastive LearningDeekshith Dade, Jake A Bergquist, Rob S MacLeod, et al.
Fertility and Sterility|July 1, 1996
Immediate postpartum insertion of the norplant contraceptive deviceJ R Molland, D B Morehead, D M Baldwin, et al.
Obstetrics and Gynecology|August 1, 1982
Artificial insemination with fresh donor semen using the cervical cap technique: a review of 278 casesC A Bergquist, J A Rock, J Miller, et al.
Computing in Cardiology|April 25, 2022
Myocardial Ischemia Detection Using Body Surface Potential Mappings and Machine LearningJames N Brundage, Vai Suliafu, Jake A Bergquist, et al.
Computing in Cardiology|August 28, 2024
Uncertainty Quantification of Fiber Orientation and Epicardial ActivationLindsay C Rupp, Anna Busatto, Jake A Bergquist, et al.
Frontiers in Physiology|June 5, 2023
Investigation into the importance of using natural PVCs and pathological models for potential-based ECGI validationLaura R Bear, Jake A Bergquist, Emma Abell, et al.
Pageof 12