Interpretable AI, Fairness & Ethics

Opening the "black box" of complex models to provide human-understandable insights while ensuring equitable outcomes and robust digital ethics.

pyFUME

A Python package for automatic Fuzzy Model Estimation from data.

Assessing Cardiac Functionality via Interpretable AI

A fully interpretable, rule-based machine learning model using myocardial strain data to accurately estimate Left Ventricular Ejection Fraction (LVEF).

FanFAIR

Semi-automatic assessment of dataset fairness using fuzzy logic.

Active Research Area

We are currently finalizing the digital portfolio for this research pillar. More detailed project descriptions, datasets, and software repositories will be published here soon.