A lightweight generative model for interpretable subject-level prediction

Chiara Mauri, Stefano Cerri, Oula Puonti, Mark Mühlau, Koen Van Leemput

Abstract: Highlights•We propose an inherently interpretable generative model for image-based prediction.•The method is also accurate, easy to use, and fast to train.•Besides predictions, it offers intuitive causal explanations of its inner workings.•We tested the method on brain age and gender prediction tasks on UK Biobank data.

External IDs:dblp:journals/mia/MauriCPML25