activity
20192022
most citedOncology and mechanics: landmark studies and promising clinical applications

7 citations · 15 across the 6 of their papers we have counts for

collaborators

7 papers

q-bio.TO20222 cited

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

Guillermo Lorenzo, Angela M. Jarrett, Christian T. Meyer +3

Neoadjuvant chemotherapy (NAC) is a standard-of-care treatment for locally advanced triple negative breast cancer (TNBC) before surgery. The early assessment of TNBC response to NA…

q-bio.TO20227 cited

Oncology and mechanics: landmark studies and promising clinical applications

Stéphane Urcun, Guillermo Lorenzo, Davide Baroli +5

Clinical management of cancer has continuously evolved for several decades. Biochemical, molecular and genomics approaches have brought and still bring numerous insights into cance…

physics.bio-ph2022

Data-driven simulation of Fisher-Kolmogorov tumor growth models using Dynamic Mode Decomposition

Alex Viguerie, Malú Grave, Gabriel F. Barros +3

The computer simulation of organ-scale biomechanistic models of cancer personalized via routinely collected clinical and imaging data enables to obtain patient-specific predictions…

q-bio.TO20216 cited

Quantitative in vivo imaging to enable tumor forecasting and treatment optimization

Guillermo Lorenzo, David A. Hormuth, Angela M. Jarrett +6

Current clinical decision-making in oncology relies on averages of large patient populations to both assess tumor status and treatment outcomes. However, cancers exhibit an inheren…

math.OC2020

Optimal control of cytotoxic and antiangiogenic therapies on prostate cancer growth

Pierluigi Colli, Hector Gomez, Guillermo Lorenzo +3

Prostate cancer can be lethal in advanced stages, for which chemotherapy may become the only viable therapeutic option. While there is no clear clinical management strategy fitting…

q-bio.PE2020

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

Alex Viguerie, Guillermo Lorenzo, Ferdinando Auricchio +6

We present an early version of a Susceptible-Exposed-Infected-Recovered-Deceased (SEIRD) mathematical model based on partial differential equations coupled with a heterogeneous dif…