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)

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)

An in silico 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)

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)

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)

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 (SC Workshops, 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)

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., 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, 2023)

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)

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)

Validating the predictions of mathematical models describing tumor growth and treatment response. - Guillermo Lorenzo; David A. Hormuth II; Chengyue Wu; Graham Pash; Anirban Chaudhuri; Ernesto A. B. F. Lima; Lois C. Okereke; Reshmi Patel; Karen Willcox; Thomas E. Yankeelov (CoRR, 2025)

TumorTwin: A python framework for patient-specific digital twins in oncology. - Michael G. Kapteyn; Anirban Chaudhuri; Ernesto A. B. F. Lima; Graham Pash; Rafael Bravo; Karen Willcox; Thomas E. Yankeelov; David A. Hormuth II (CoRR, 2025)

Predictive Digital Twins with Quantified Uncertainty for Patient-Specific Decision Making in Oncology. - Graham Pash; Umberto Villa; David A. Hormuth II; Thomas E. Yankeelov; Karen Willcox (CoRR, 2025)