GLioblastoma Image Analysis for integrating brain tumor growth models with medical imaging
Common biochemical and topological attributes of metabolic genes recurrently dysregulated in tumors.
Physics-informed and pure-mechanistic Universal Differential Equations (UDEs) for modeling tumor–immune dynamics. Dual Julia pipelines: Enhanced PI-NODE with residual/correction subnetworks for hybrid physics-neural learning, and Pure-Mechanistic UDE with biologically-constrained Gompertz growth and saturating immune-killing.
Tractography-based stochastic mathematical model of glioblastoma invasion
A python code/package for a cellular automaton modeling tumor growth. The user can set the parameters, create unique initial states, view statistics, save data and also use a streamlit dashboard as a graphical interface. Growth plots, histograms and animation is available for visualization in an easy to use way.
Combines use of a Genetic Algorithm to control immunotherapy dosing in the Kirschner-Panetta Model.
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