tumor-growth

Code for deep learning-based glioma/tumor growth models

🧠 Growth dynamics of untreated meningiomas

3D-1D tumor growth model for simulation of angiogenesis

A short overview of my bachelor thesis

Simple mixed-effects growth models applied to tumor growth (modeling the effect of treatment and measurement method)

Набор инструментов для обработки радиобиологических Excel‑данных: визуализация опухолевого роста и кожных реакций, статистика, интерактивный GUI (PyQt6). Поддерживается оценка параметров LQ‑модели (α/β) и сравнение экспериментов.

Tumor growth simulation using 2D cellular automaton

Implementation of a mammary tumor growth ODE model.

Source codes to simulate tumor growth in interaction with immune cell in a size and space structured tumor-immune interaction model and to perform sensitivity analysis of the stationary profile.

Project on ABM tumor growth for the Agent-Based Modeling course at the UvA 2023-2024

[ECCV 2026] Physics-Grounded Disentangled Flow Modeling for Brain Disease Progression Trajectory

Matplotlib mice tumor analysis of drug effectiveness for cancer research.

Computational simulation of PLGA nanoparticle transport, drug release, and tumor response using finite difference methods in Python.

Fisher-Kolmogorov reaction-diffusion model for simulating glioma invasion: 1D/2D/3D solvers with anisotropic diffusion and therapy simulation

CT-informed biomechanical simulation of mesothelioma tumour growth with the finite element method (DolfinX, GMSH).

Predict the effect of genetic mutations in cancer tumors and classify them based on text clinical literature.

A naive extension and analysis of a DE system describing the interactions between tumor cells, effector cells, HTCs, and iNKT cells

Neural networks for structured data classification and multi-horizon time series forecasting; heart disease risk, weather, Lorenz chaos, and tumor growth. Deep Learning Research Internship, Universität Koblenz.

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.

Tumor growth simulation using MRI imaging data and mathematical growth models for computational oncology research.