Methods from machine learning and AI have extremely powerful data modelling in the last years.
The goal of this project is to use interpretable methods/models to find and assess causality between non-medical features and target features i.e. diagnosis - this would be the column CDR (Clinical Dementia Rating) for the dementia dataset, and diagnosis for the breast cancer dataset.
At center of this project is the storytelling. Using the right kind of models, and more importantly visualizations of the data and results, in order to communicate our insights aptly.