A comparative study of pre-trained language models for named entity recognition in clinical trial eligibility criteria from multiple corpora.

Findings from this study not only demonstrate the importance of contextual embeddings trained from domain-specific corpora, but also shed lights on the benefits of leveraging multiple data sources for the challenging NER task in clinical trial eligibility criteria text.