Cancer Tumour Modeling with Magnetic Nanoparticles
- mathematical modeling
- Bayesian
- MCMC
- scikit-learn
What it is
A computational framework for modeling tumor dynamics in the presence of magnetic nanoparticles. It couples a mechanistic PDE/ODE model of nanoparticle diffusion, binding, and internalization with:
- Bayesian inference (MCMC via emcee) for parameter estimation and uncertainty quantification, and
- machine-learning predictors — Gaussian Process Regression, Random Forest, and Gradient Boosting — all trained/tested on a consistent 75/25 split with comparison plots.
Includes datasets for multiple treatment groups and scripts that regenerate every figure in the manuscript.
Stack
Python · SciPy · emcee · corner · scikit-learn (GPR/RF/GBM)