Publicaciones en colaboración con investigadores/as de University of Texas at Austin (32)

2024

  1. 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

    Engineering with Computers, Vol. 40, Núm. 3, pp. 1469-1499

  2. A mathematical model for predicting the spatiotemporal response of breast cancer cells treated with doxorubicin

    Cancer Biology and Therapy, Vol. 25, Núm. 1

  3. Designing clinical trials for patients who are not average

    iScience, Vol. 27, Núm. 1

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

    Engineering with Computers, Vol. 40, Núm. 2, pp. 813-837

  5. MATHEMATICAL ANALYSIS OF A MODEL-CONSTRAINED INVERSE PROBLEM FOR THE RECONSTRUCTION OF EARLY STATES OF PROSTATE CANCER GROWTH

    SIAM Journal on Applied Mathematics, Vol. 84, Núm. 5, pp. 2000-2027

  6. Patient-Specific, Mechanistic Models of Tumor Growth Incorporating Artificial Intelligence and Big Data

    Annual review of biomedical engineering, Vol. 26, Núm. 1, pp. 529-560

2022

  1. A Petrov-Galerkin method for nonlocal convection-dominated diffusion problems

    Journal of Computational Physics, Vol. 452

  2. Data-driven simulation of fisher kolmogorov tumor growth models using dynamic mode decomposition

    Journal of Biomechanical Engineering, Vol. 144, Núm. 12

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

    Frontiers in Molecular Biosciences, Vol. 9

  4. Oncology and mechanics: Landmark studies and promising clinical applications

    Advances in Applied Mechanics (Academic Press Inc.), pp. 513-571

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

    iScience, Vol. 25, Núm. 11

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

    IEEE Transactions on Biomedical Engineering, Vol. 69, Núm. 11, pp. 3334-3344

2021

  1. Biologically-based mathematical modeling of tumor vasculature and angiogenesis via time-resolved imaging data

    Cancers, Vol. 13, Núm. 12

  2. Math, magnets, and medicine: enabling personalized oncology

    Expert Review of Precision Medicine and Drug Development

  3. Optimal control of cytotoxic and antiangiogenic therapies on prostate cancer growth

    Mathematical Models and Methods in Applied Sciences, Vol. 31, Núm. 7, pp. 1419-1468

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

    Applied Mathematics Letters, Vol. 111

2020

  1. A numerical simulation study of the dual role of 5α-reductase inhibitors on tumor growth in prostates enlarged by benign prostatic hyperplasia via stress relaxation and apoptosis upregulation

    Computer Methods in Applied Mechanics and Engineering, Vol. 362

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

    Computational Mechanics, Vol. 66, Núm. 5, pp. 1131-1152

  3. Integrating Quantitative Assays with Biologically Based Mathematical Modeling for Predictive Oncology

    iScience, Vol. 23, Núm. 12

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

    IEEE Transactions on Medical Imaging, Vol. 39, Núm. 9, pp. 2760-2771