Pages that link to "Item:Q2309845"
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The following pages link to A fully coupled space-time multiscale modeling framework for predicting tumor growth (Q2309845):
Displaying 13 items.
- Toward predictive multiscale modeling of vascular tumor growth, computational and experimental oncology for tumor prediction (Q525356) (← links)
- A nonlinear poroelastic theory of solid tumors with glycosaminoglycan swelling (Q1749006) (← links)
- Coupling brain-tumor biophysical models and diffeomorphic image registration (Q1987828) (← links)
- A-SLEIPNNIR: a multiscale, anisotropic adaptive, particle level set framework for moving interfaces. Transport equation applications (Q2002455) (← links)
- In silico investigations of intratumoral heterogeneous interstitial fluid pressure (Q2041320) (← links)
- PDE-constrained optimization in medical image analysis (Q2071424) (← links)
- Supermodeling, a convergent data assimilation meta-procedure used in simulation of tumor progression (Q2122649) (← links)
- Interpreting stochastic agent-based models of cell death (Q2175264) (← links)
- Three-dimensional image-based mechanical modeling for predicting the response of breast cancer to neoadjuvant therapy (Q2310378) (← links)
- Simulation of glioblastoma growth using a 3D multispecies tumor model with mass effect (Q2315208) (← links)
- MODELLING THREE-DIMENSIONAL GROWTH OF BRAIN TUMOURS FROM TIME SERIES OF SCANS (Q4933725) (← links)
- Iterated Numerical Homogenization for MultiScale Elliptic Equations with Monotone Nonlinearity (Q5022753) (← links)
- Bridging scales: a hybrid model to simulate vascular tumor growth and treatment response (Q6201151) (← links)
