SOURCE-LINKED INTELLIGENCE

CHILD: Human-in-the-Loop OOD Detection for Safe Clinical Deployment

arXiv · AI, language, vision and robotics · article · Sep 7, 2026 · UTC

Out-of-distribution (OOD) detection is critical for safe deployment of medical AI systems. Recently, test-time adaptation (TTA) has emerged as a new paradigm for OOD detection, automatically adjusting detector behavior during deployment. However, such automatic adaptation mechanisms may raise safety concerns in safety-critical clinical environments. While physician oversight can mitigate these risks, it is resource-intensive and must be judiciously allocated. To reconcile safety with efficiency, we propose CHILD, a training-free framework designed to enhance streaming OOD detection via sparse

Read original source ↗ Open in workspace

recordType

paper

region

Global