Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

David A Hormuth

Showing results (11-20 of 72) with videos related to

Pageof 8
Sort By:
Magnetic Resonance in Medicine|October 29, 2018
Quantitative analysis of vascular properties derived from ultrafast DCE-MRI to discriminate malignant and benign breast tumorsChengyue Wu, Federico Pineda, David A Hormuth, et al.
JCO Clinical Cancer Informatics|May 8, 2026
Simulating Cancer Recurrence Patterns From Post-Treatment Viable Tumor Burden DistributionsMohammad U Zahid, Joseph D Butner, David M Swanson, et al.
Journal of Medical Imaging (Bellingham, Wash.)|March 11, 2024
Systematic evaluation of MRI-based characterization of tumor-associated vascular morphology and hemodynamics via a dynamic digital phantomChengyue Wu, David A Hormuth, Ty Easley, et al.
Scientific Reports|June 27, 2023
Comparing mechanism-based and machine learning models for predicting the effects of glucose accessibility on tumor cell proliferationJianchen Yang, Jack Virostko, Junyan Liu, et al.
Scientific Reports|April 20, 2021
Image-based personalization of computational models for predicting response of high-grade glioma to chemoradiationDavid A Hormuth, Karine A Al Feghali, Andrew M Elliott, et al.
Gigabyte (Hong Kong, China)|March 23, 2023
PhysiCOOL: A generalized framework for model Calibration and Optimization Of modeLing projectsInês G Gonçalves, David A Hormuth, Sandhya Prabhakaran, et al.
Methods in Molecular Biology (Clifton, N.J.)|January 19, 2018
Mechanically Coupled Reaction-Diffusion Model to Predict Glioma Growth: Methodological DetailsDavid A Hormuth, Stephanie L Eldridge, Jared A Weis, et al.
Brain Multiphysics|January 8, 2024
Predicting the spatio-temporal response of recurrent glioblastoma treated with rhenium-186 labelled nanoliposomesChase Christenson, Chengyue Wu, David A Hormuth, et al.
IEEE Transactions on Medical Imaging|April 14, 2023
Bayesian Inference of Tissue Heterogeneity for Individualized Prediction of Glioma GrowthBaoshan Liang, Jingye Tan, Luke Lozenski, et al.
Plos One|July 13, 2021
An experimental-mathematical approach to predict tumor cell growth as a function of glucose availability in breast cancer cell linesJianchen Yang, Jack Virostko, David A Hormuth, et al.
Pageof 8

Showing results (11-20 of 72) with videos related to

Sort By:
Pageof 8
Magnetic Resonance in Medicine|October 29, 2018
Quantitative analysis of vascular properties derived from ultrafast DCE-MRI to discriminate malignant and benign breast tumorsChengyue Wu, Federico Pineda, David A Hormuth, et al.
JCO Clinical Cancer Informatics|May 8, 2026
Simulating Cancer Recurrence Patterns From Post-Treatment Viable Tumor Burden DistributionsMohammad U Zahid, Joseph D Butner, David M Swanson, et al.
Journal of Medical Imaging (Bellingham, Wash.)|March 11, 2024
Systematic evaluation of MRI-based characterization of tumor-associated vascular morphology and hemodynamics via a dynamic digital phantomChengyue Wu, David A Hormuth, Ty Easley, et al.
Scientific Reports|June 27, 2023
Comparing mechanism-based and machine learning models for predicting the effects of glucose accessibility on tumor cell proliferationJianchen Yang, Jack Virostko, Junyan Liu, et al.
Scientific Reports|April 20, 2021
Image-based personalization of computational models for predicting response of high-grade glioma to chemoradiationDavid A Hormuth, Karine A Al Feghali, Andrew M Elliott, et al.
Gigabyte (Hong Kong, China)|March 23, 2023
PhysiCOOL: A generalized framework for model Calibration and Optimization Of modeLing projectsInês G Gonçalves, David A Hormuth, Sandhya Prabhakaran, et al.
Methods in Molecular Biology (Clifton, N.J.)|January 19, 2018
Mechanically Coupled Reaction-Diffusion Model to Predict Glioma Growth: Methodological DetailsDavid A Hormuth, Stephanie L Eldridge, Jared A Weis, et al.
Brain Multiphysics|January 8, 2024
Predicting the spatio-temporal response of recurrent glioblastoma treated with rhenium-186 labelled nanoliposomesChase Christenson, Chengyue Wu, David A Hormuth, et al.
IEEE Transactions on Medical Imaging|April 14, 2023
Bayesian Inference of Tissue Heterogeneity for Individualized Prediction of Glioma GrowthBaoshan Liang, Jingye Tan, Luke Lozenski, et al.
Plos One|July 13, 2021
An experimental-mathematical approach to predict tumor cell growth as a function of glucose availability in breast cancer cell linesJianchen Yang, Jack Virostko, David A Hormuth, et al.
Pageof 8