PERFECTO: Prediction of Extended Response and Growth Functions for Estimating Chemotherapy Outcomes in Breast Cancer
PERFECTO Codebase:
datasets - the experimental datasets (csv files) and their source, each in separate directories
models - codebase to run and reproduce the experiments
Directory structure:
models/PERFECTO/.
- create_init_network.m - init PERFECTO network (SOM + HL)
- error_std.m - error std calculation function
- PERFECTO_core.m - main script to run PERFECTO
- model_rmse.m - RMSE calculation function
- model_sse.m - SSE calculation function
- parametrize_learning_law.m - function to parametrize PERFECTO learning
- present_tuning_curves.m - function to visualize PERFECTO SOM tuning curves
- randnum_gen.m - weight initialization function
- tumor_growth_model_fit.m - function implementing ODE models
- tumor_growth_models_eval.m - main evaluation on PERFECTO runtime
- visualize_results.m - visualize PERFECTO output and internals
- visualize_runtime.m - visualize PERFECTO runtime
Usage:
models/PERFECTO/perfecto_core.m - main function that runs PERFECTO and generates the runtime output file (mat file)
models/PERFECTO/tumor_growth_models_eval.m - evaluation and plotting function reading the PERFECTO runtime output file