Semantically Describing Predictive Models for Interpretable Insights into Lung Cancer Relapse [Entwurf]

SemDesLC predicts lung cancer relapse likelihood, providing oncologists with patient-centric and population-centric analysis. Our approach bridge the gap and fulfill the needs of three different type of users: KG builders, analysts and consumers. This repository contains all the necessary scripts and instructions to reproduce the experiments.