AI RESEARCH
HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering
arXiv CS.AI
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ArXi:2604.21027v1 Announce Type: new Electronic health record (EHR) question answering is often handled by LLM-based pipelines that are costly to deploy and do not explicitly leverage the hierarchical structure of clinical data. Motivated by evidence that medical ontologies and patient trajectories exhibit hyperbolic geometry, we propose HypEHR, a compact Lorentzian model that embeds codes, visits, and questions in hyperbolic space and answers queries via geometry-consistent cross-attention with type-specific pointer heads.