project Details

We rely on machine learning models, data visualization techniques, and Shiny for developing the graphical user interface.

Exploratory Data Analysis Machine Learning Graphical Interface

Results:

This project received a grade of 17.5 out of 20, delivering robust and comprehensive analyses that effectively address the questions posed.

Prediction of Technical Failure in Peritoneal Dialysis

This was my end-of-year project (second year) and it involved several stages:

  • A literature review to identify the variables to collect
  • Data collection and preprocessing
  • Determination of the most impactful variables
  • A scientific publication : lien