By Julien Balbierer and Benjamin Nicol
Directed by Asst. Prof. Natalia Diaz-Rodriguez (ENSTA)
The goal of this research project is to improve eXplainable AI (XAI) methods by improving its robustness and trust. The application will be on COVID-19 diagnosis on X-ray images.
The dataset used for this project is COVIDGR 1.0.
COVIDGR is a set of X-ray images to assist the diagnosis of COVID-19 built in close collaboration with radiology expert teams in Spain.
In order to run correctly the notebooks, create a virtual environment and then install the requierements.
requirements.txtfor pipenv.ymlfor conda