Cargando…
Quantifying Uncertainty and Robustness in a Biomathematical Model–Based Patient-Specific Response Metric for Glioblastoma
PURPOSE: Glioblastomas, lethal primary brain tumors, are known for their heterogeneity and invasiveness. A growing body of literature has been developed demonstrating the clinical relevance of a biomathematical model, the proliferation-invasion model, of glioblastoma growth. Of interest here is the...
Autores principales: | Hawkins-Daarud, Andrea, Johnston, Sandra K., Swanson, Kristin R. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society of Clinical Oncology
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6633916/ https://www.ncbi.nlm.nih.gov/pubmed/30758984 http://dx.doi.org/10.1200/CCI.18.00066 |
Ejemplares similares
-
Image-based metric of invasiveness predicts response to adjuvant temozolomide for primary glioblastoma
por: Massey, Susan Christine, et al.
Publicado: (2020) -
A biomathematical model of atherosclerosis in mice
por: Schirm, Sibylle, et al.
Publicado: (2022) -
Uncertainty quantification in the radiogenomics modeling of EGFR amplification in glioblastoma
por: Hu, Leland S., et al.
Publicado: (2021) -
Stochastic biomathematical models: with applications to neuronal modeling
por: Bachar, Mostafa, et al.
Publicado: (2013) -
In silico analysis suggests differential response to bevacizumab and radiation combination therapy in newly diagnosed glioblastoma
por: Hawkins-Daarud, Andrea, et al.
Publicado: (2015)