David A. Hormuth

According to our database, David A. Hormuth authored at least 11 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Fast model calibration for predicting the response of breast cancer to chemotherapy using proper orthogonal decomposition.

Chase Christenson, Chengyue Wu, David A. Hormuth, Casey E. Stowers, Megan LaMonica, Jingfei Ma, Gaiane M. Rauch, Thomas E. Yankeelov

J. Comput. Sci., 2024

Image-guided patient-specific optimization of catheter placement for convection-enhanced nanoparticle delivery in recurrent glioblastoma.

Chengyue Wu, David A. Hormuth, Chase Christenson, Ryan T. Woodall, Michael R. A. Abdelmalik, William T. Phillips, Thomas J. R. Hughes, Andrew J. Brenner, Thomas E. Yankeelov

Comput. Biol. Medicine, 2024

2023

Bayesian Inference of Tissue Heterogeneity for Individualized Prediction of Glioma Growth.

Baoshan Liang, Jingye Tan, Luke Lozenski, David A. Hormuth, Thomas E. Yankeelov, Umberto Villa, Danial Faghihi

IEEE Trans. Medical Imaging, October, 2023

Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas.

Anirban Chaudhuri, Graham Pash, David A. Hormuth, Guillermo Lorenzo, Michael G. Kapteyn, Chengyue Wu, Ernesto A. B. F. Lima, Thomas E. Yankeelov, Karen Willcox

Frontiers Artif. Intell., February, 2023

Patient-specific, mechanistic models of tumor growth incorporating artificial intelligence and big data.

Guillermo Lorenzo, Syed Rakin Ahmed, David A. Hormuth II, Brenna Vaughn, Jayashree Kalpathy-Cramer, Luis Solorio, Thomas E. Yankeelov, Héctor Gómez

CoRR, 2023

Optimized Patient-Specific Catheter Placement for Convection-Enhanced Nanoparticle Delivery in Recurrent Glioblastoma.

Chengyue Wu, David A. Hormuth, Chase Christenson, Ryan T. Woodall, Michael R. A. Abdelmalik, William T. Phillips, Thomas J. R. Hughes, Andrew J. Brenner, Thomas E. Yankeelov

Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

2022

Towards Patient-Specific Optimization of Neoadjuvant Treatment Protocols for Breast Cancer Based on Image-Guided Fluid Dynamics.

Chengyue Wu, David A. Hormuth, Guillermo Lorenzo, Angela M. Jarrett, Federico Pineda, Frederick M. Howard, Gregory S. Karczmar, Thomas E. Yankeelov

IEEE Trans. Biomed. Eng., 2022

2021

Modeling of Glioma Growth With Mass Effect by Longitudinal Magnetic Resonance Imaging.

Birkan Tunç, David A. Hormuth II, George Biros, Thomas E. Yankeelov

IEEE Trans. Biomed. Eng., 2021

An <i>in silico</i> validation framework for quantitative DCE-MRI techniques based on a dynamic digital phantom.

Chengyue Wu, David A. Hormuth II, Ty Easley, Victor Eijkhout, Federico Pineda, Gregory S. Karczmar, Thomas E. Yankeelov

Medical Image Anal., 2021

Quantitative in vivo imaging to enable tumor forecasting and treatment optimization.

Guillermo Lorenzo, David A. Hormuth II, Angela M. Jarrett, Ernesto A. B. F. Lima, Shashank Subramanian, George Biros, J. Tinsley Oden, Thomas J. R. Hughes, Thomas E. Yankeelov

CoRR, 2021

2020

Patient-Specific Characterization of Breast Cancer Hemodynamics Using Image-Guided Computational Fluid Dynamics.

Chengyue Wu, David A. Hormuth, Todd A. Oliver, Federico Pineda, Guillermo Lorenzo, Gregory S. Karczmar, Robert D. Moser, Thomas E. Yankeelov

IEEE Trans. Medical Imaging, 2020