AI RESEARCH
REN: Anatomically-Informed Mixture-of-Experts for Interstitial Lung Disease Diagnosis
arXiv CS.AI
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ArXi:2510.04923v3 Announce Type: replace-cross Mixture-of-Experts (MoE) architectures achieve scalable learning by routing inputs to specialized subnetworks through conditional computation. However, conventional MoE designs assume homogeneous expert capability and domain-agnostic routing-assumptions that are fundamentally misaligned with medical imaging, where anatomical structure and regional disease heterogeneity govern pathological patterns. We