Explainability and uncertainty: Two sides of the same coin for enhancing the interpretability of deep learning models in healthcare

Massimo Salvi, Silvia Seoni, Andrea Campagner, Arkadiusz Gertych, U. Rajendra Acharya, Filippo Molinari, Federico Cabitza

Abstract: Highlights•We propose the merging of uncertainty measures with explainable AI in healthcare.•Uncertainty quantification is used to assess AI explanation reliability.•The XAI-UQ integration enhances trust in medical AI decision making.