SNOMED-CT graph embeddings via random walks and Poincaré methods yield 5-6x better concept similarity and 6-20% better patient diagnosis prediction than prior embeddings.
Gram: graph-based attention model for healthcare representation learning
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Snomed2Vec: Random Walk and Poincar\'e Embeddings of a Clinical Knowledge Base for Healthcare Analytics
SNOMED-CT graph embeddings via random walks and Poincaré methods yield 5-6x better concept similarity and 6-20% better patient diagnosis prediction than prior embeddings.