G. Lorenzo

发表

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

Thomas E. Yankeelov, J. Tinsley Oden, Thomas J. R. Hughes, 2021, ArXiv.

Simulating the spread of COVID-19 via a spatially-resolved susceptible–exposed–infected–recovered–deceased (SEIRD) model with heterogeneous diffusion

Thomas E. Yankeelov, Guillermo Lorenzo, Alessandro Reali, 2020, Applied Mathematics Letters.

Hierarchically refined and coarsened splines for moving interface problems, with particular application to phase-field models of prostate tumor growth

Thomas J. R. Hughes, Kevin Tew, Michael A. Scott, 2017 .

Strategies for local re nement and coarsening of hierarchical splines with particular application to phase-eld models of prostate tumor growth

T. Hughes, M. Scott, G. Lorenzo, 2016 .

Mechanistic modelling of PSA dynamics shows potential for personalised prediction of radiation therapy outcome

A. Reali, V. Pérez-García, G. Lorenzo, 2019 .

Integrating mechanism-based modeling with biomedical imaging to build practical digital twins for clinical oncology.

T. Yankeelov, D. Patt, G. Lorenzo, 2022, Biophysics reviews.

Oncology and mechanics: landmark studies and promising clinical applications

W. Skalli, P. Rohan, G. Lorenzo, 2022, ArXiv.

Identifying mechanisms driving the early response of triple negative breast cancer patients to neoadjuvant chemotherapy using a mechanistic model integrating in vitro and in vivo imaging data

Angela M. Jarrett, T. Yankeelov, V. Quaranta, 2022, ArXiv.

Integrating Quantitative Assays with Biologically Based Mathematical Modeling for Predictive Oncology

Guillermo Lorenzo, Kaitlyn E. Johnson, Angela M. Jarrett, 2020, iScience.

Mechanistic modelling of prostate-specific antigen dynamics shows potential for personalized prediction of radiation therapy outcome

Alessandro Reali, Víctor M. Pérez-García, Hector Gomez, 2019, Journal of the Royal Society Interface.

Math, magnets, and medicine: enabling personalized oncology

Angela M. Jarrett, T. Yankeelov, D. Patt, 2021, Expert review of precision medicine and drug development.

Biologically-Based Mathematical Modeling of Tumor Vasculature and Angiogenesis via Time-Resolved Imaging Data

Angela M. Jarrett, J. Oden, T. Yankeelov, 2021, Cancers.

Optimal control of cytotoxic and antiangiogenic therapies on prostate cancer growth pdf

Alessandro Reali, Pierluigi Colli, Elisabetta Rocca, 2020, Mathematical Models and Methods in Applied Sciences.

A numerical simulation study of the dual role of5α-reductase inhibitors on tumor growth in prostates enlarged by benign prostatic hyperplasia via stress relaxation and apoptosis upregulation

H. Gomez, A. Reali, T. J. R. Hughes, 2020 .

Mathematical analysis and simulation study of a phase-field model of prostate cancer growth with chemotherapy and antiangiogenic therapy effects pdf

Pierluigi Colli, Elisabetta Rocca, Gabriela Marinoschi, 2019, Mathematical Models and Methods in Applied Sciences.

Computer simulations suggest that prostate enlargement due to benign prostatic hyperplasia mechanically impedes prostate cancer growth

Alessandro Reali, Thomas J. R. Hughes, Hector Gomez, 2019, Proceedings of the National Academy of Sciences.

Tissue-scale, personalized modeling and simulation of prostate cancer growth

Guillermo Lorenzo, Yongjie Jessica Zhang, Kevin Tew, 2016, Proceedings of the National Academy of Sciences.

Data-Driven Simulation of Fisher-Kolmogorov Tumor Growth Models Using Dynamic Mode Decomposition.

Gabriel F. Barros, A. Reali, A. Coutinho, 2022, Journal of biomechanical engineering.

Mathematical characterization of population dynamics in breast cancer cells treated with doxorubicin

T. Yankeelov, A. Brock, G. Lorenzo, 2021, bioRxiv.

Diffusion–reaction compartmental models formulated in a continuum mechanics framework: application to COVID-19, mathematical analysis, and numerical study

T. Hughes, T. Yankeelov, F. Auricchio, 2020, Computational Mechanics.

Dynamic parameterization of a modified SEIRD model to analyze and forecast the dynamics of COVID-19 outbreaks in the United States

T. Yankeelov, G. Lorenzo, Alex Viguerie, 2023, Engineering with computers.

Patient-specific forecasting of postradiotherapy prostate-specific antigen kinetics enables early prediction of biochemical relapse

A. Reali, F. Montorsi, A. Briganti, 2022, medRxiv.

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

Guillermo Lorenzo, Todd A. Oliver, Chengyue Wu, 2020, IEEE Transactions on Medical Imaging.

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

T. Yankeelov, Jayashree Kalpathy-Cramer, G. Lorenzo, 2023, ArXiv.

Patient-specific computational forecasting of prostate cancer growth during active surveillance using an imaging-informed biomechanistic model

Jon S. Heiselman, T. Yankeelov, M. Miga, 2023, ArXiv.

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

Michael G. Kapteyn, T. Yankeelov, K. Willcox, 2023, Frontiers in artificial intelligence.

A global sensitivity analysis of a mechanistic model of neoadjuvant chemotherapy for triple negative breast cancer constrained by in vitro and in vivo imaging data

T. Yankeelov, V. Quaranta, D. Tyson, 2023, Engineering with Computers.

A Pilot Study on Patient-specific Computational Forecasting of Prostate Cancer Growth during Active Surveillance Using an Imaging-informed Biomechanistic Model

Jon S. Heiselman, T. Yankeelov, A. Reali, 2024, Cancer research communications.