ClinicalBERT
Related Papers
Does BERT Pretrained on Clinical Notes Reveal Sensitive Data?
AbstractLarge Transformers pretrained over clinical notes from Electronic Health Records (EHR) have afforded substantial gains in performance on predictive clinical tasks. The cost of training such models (and the necessity …...
Probing Pre-Trained Language Models for Disease Knowledge
Pre-trained language models such as Clini- calBERT have achieved impressive results on tasks such as medical Natural Language In- ference. At first glance, this may suggest that these models are …...
Self-Supervised Detection of Contextual Synonyms in a Multi-Class Setting: Phenotype Annotation Use Case
AbstractContextualised word embeddings is a powerful tool to detect contextual synonyms. However, most of the current state-of-the-art (SOTA) deep learning concept extraction methods remain supervised and underexploit the potential of …...
Zero-shot Medical Entity Retrieval without Annotation: Learning From Rich Knowledge Graph Semantics
Medical entity retrieval is an integral compo- nent for understanding and communicating in- formation across various health systems. Cur- rent approaches tend to work well on specific medical domains but …...