SOURCE-LINKED INTELLIGENCE

Explainable Uncertainty Estimation for Reliable Medical AI

arXiv · AI, language, vision and robotics · article · Aug 28, 2026 · UTC

Artificial intelligence has strong potential to support clinical decision-making, yet its adoption in healthcare remains limited due to a lack of trust. Uncertainty estimation can signal unreliable predictions, and explainable AI (XAI) can clarify how predictions are made but existing methods treat them separately, providing no feature-level insight into why a prediction is uncertain or which tests to prioritize to reduce it. To address this gap, we propose explainable uncertainty estimation, which unifies uncertainty estimation and XAI to both quantify uncertainty and explain feature-level co

Read original source ↗ Open in workspace

recordType

paper

region

Global