Papers by Hussam Kaka

1 papers
UmlsBERT: Clinical Domain Knowledge Augmentation of Contextual Embeddings Using the Unified Medical Language System Metathesaurus (2021.naacl-main)

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Challenge: Contextual word embedding models do not take into account structured expert domain knowledge from a knowledge base.
Approach: They propose a contextual embedding model that integrates domain knowledge during the pre-training process via a novel knowledge augmentation strategy.
Outcome: The proposed model outperforms existing domain-specific models on common named-entity recognition (NER) and clinical natural language inference tasks.

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