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A Causal Network Model to Estimate the Cardiotoxic Effect of Oncological Treatments in Young Breast Cancer Survivors

Introduction

This repository contains the code and data used to estimate the cardiotoxic effect of oncological treatments in young breast cancer survivors.

The code is written in R. The code is organized in the following way:

  • main.R is the main script that runs the analysis.
  • Dockerfile is the file used to create the Docker image.
  • renv.lock is the file used to create the R environment.

Usage

If you have Docker installed, then, you can run the following command:

docker build -t cvds:latest .
docker run cvds:latest

If you don't want to use Docker, you can run the following command:

R -e 'install.packages("renv"); renv::restore()'
Rscript main.R

Graphical User Interface (GUI)

The folder gui contains the code to run the graphical user interface (GUI) to estimate the cardiotoxic effect of oncological treatments in young breast cancer survivors. The GUI is written in Python using the pysmile package. Run the main.py script to start the GUI.

Citations

  • Bernasconi, Alice, et al. "A Causal Network Model to Estimate the Cardiotoxic Effect of Oncological Treatments in Young Breast Cancer Survivors." Progress in Artificial Intelligence (2024): 1-13.
  • Bernasconi, Alice, et al. "From Real-World Data to Causally Interpretable Models: A Bayesian Network to Predict Cardiovascular Diseases in Adolescents and Young Adults with Breast Cancer." Cancers 16.21 (2024): 3643.