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Plos One
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July 13, 2021
An experimental-mathematical approach to predict tumor cell growth as a function of glucose availability in breast cancer cell lines
Jianchen Yang, Jack Virostko, David A Hormuth, et al.
Physics in Medicine and Biology
|
April 27, 2018
Incorporating drug delivery into an imaging-driven, mechanics-coupled reaction diffusion model for predicting the response of breast cancer to neoadjuvant chemotherapy: theory and preliminary clinical results
Angela M Jarrett, David A Hormuth, Stephanie L Barnes, et al.
Medical Image Analysis
|
July 30, 2021
An in silico validation framework for quantitative DCE-MRI techniques based on a dynamic digital phantom
Chengyue Wu, David A Hormuth, Ty Easley, et al.
Advanced Drug Delivery Reviews
|
June 2, 2022
Opportunities for improving brain cancer treatment outcomes through imaging-based mathematical modeling of the delivery of radiotherapy and immunotherapy
David A Hormuth, Maguy Farhat, Chase Christenson, et al.
International Journal of Radiation Oncology, Biology, Physics
|
February 6, 2018
Biophysical Modeling of In Vivo Glioma Response After Whole-Brain Radiation Therapy in a Murine Model of Brain Cancer
David A Hormuth, Jared A Weis, Stephanie L Barnes, et al.
Magnetic Resonance in Medicine
|
November 9, 2017
The effects of intravoxel contrast agent diffusion on the analysis of DCE-MRI data in realistic tissue domains
Ryan T Woodall, Stephanie L Barnes, David A Hormuth, et al.
Journal of Computational Science
|
April 30, 2025
Fast model calibration for predicting the response of breast cancer to chemotherapy using proper orthogonal decomposition
Chase Christenson, Chengyue Wu, David A Hormuth, et al.
JCO Clinical Cancer Informatics
|
February 27, 2019
Mechanism-Based Modeling of Tumor Growth and Treatment Response Constrained by Multiparametric Imaging Data
David A Hormuth, Angela M Jarrett, Ernesto A B F Lima, et al.
Journal of the Royal Society, Interface
|
March 24, 2017
A mechanically coupled reaction-diffusion model that incorporates intra-tumoural heterogeneity to predict <i>in vivo</i> glioma growth
David A Hormuth, Jared A Weis, Stephanie L Barnes, et al.
Annual Review of Biomedical Engineering
|
April 10, 2024
Patient-Specific, Mechanistic Models of Tumor Growth Incorporating Artificial Intelligence and Big Data
Guillermo Lorenzo, Syed Rakin Ahmed, David A Hormuth, et al.
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of 8
Search research articles
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Showing results (21-30 of 73) with videos related to
Sort By:
Page
of 8
Plos One
|
July 13, 2021
An experimental-mathematical approach to predict tumor cell growth as a function of glucose availability in breast cancer cell lines
Jianchen Yang, Jack Virostko, David A Hormuth, et al.
Physics in Medicine and Biology
|
April 27, 2018
Incorporating drug delivery into an imaging-driven, mechanics-coupled reaction diffusion model for predicting the response of breast cancer to neoadjuvant chemotherapy: theory and preliminary clinical results
Angela M Jarrett, David A Hormuth, Stephanie L Barnes, et al.
Medical Image Analysis
|
July 30, 2021
An in silico validation framework for quantitative DCE-MRI techniques based on a dynamic digital phantom
Chengyue Wu, David A Hormuth, Ty Easley, et al.
Advanced Drug Delivery Reviews
|
June 2, 2022
Opportunities for improving brain cancer treatment outcomes through imaging-based mathematical modeling of the delivery of radiotherapy and immunotherapy
David A Hormuth, Maguy Farhat, Chase Christenson, et al.
International Journal of Radiation Oncology, Biology, Physics
|
February 6, 2018
Biophysical Modeling of In Vivo Glioma Response After Whole-Brain Radiation Therapy in a Murine Model of Brain Cancer
David A Hormuth, Jared A Weis, Stephanie L Barnes, et al.
Magnetic Resonance in Medicine
|
November 9, 2017
The effects of intravoxel contrast agent diffusion on the analysis of DCE-MRI data in realistic tissue domains
Ryan T Woodall, Stephanie L Barnes, David A Hormuth, et al.
Journal of Computational Science
|
April 30, 2025
Fast model calibration for predicting the response of breast cancer to chemotherapy using proper orthogonal decomposition
Chase Christenson, Chengyue Wu, David A Hormuth, et al.
JCO Clinical Cancer Informatics
|
February 27, 2019
Mechanism-Based Modeling of Tumor Growth and Treatment Response Constrained by Multiparametric Imaging Data
David A Hormuth, Angela M Jarrett, Ernesto A B F Lima, et al.
Journal of the Royal Society, Interface
|
March 24, 2017
A mechanically coupled reaction-diffusion model that incorporates intra-tumoural heterogeneity to predict <i>in vivo</i> glioma growth
David A Hormuth, Jared A Weis, Stephanie L Barnes, et al.
Annual Review of Biomedical Engineering
|
April 10, 2024
Patient-Specific, Mechanistic Models of Tumor Growth Incorporating Artificial Intelligence and Big Data
Guillermo Lorenzo, Syed Rakin Ahmed, David A Hormuth, et al.
Page
of 8