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Discrete Neural Interlingua for Ontology-Agnostic EHR Modeling

Ding, Tong et al.
arXiv (All) · Papers
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artificial-intelligencecomputation-and-languagemachine-learning
EHR foundation models promise scalable clinical prediction across health systems, yet their deployment is constrained by a tokenization bottleneck. The same clinical concept can appear as different ontology codes, local identifiers, synonyms, or free-text descriptions, which standard EHR tokenizers
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