Surf at MEDIQA 2019: Improving Performance of Natural Language Inference in the Clinical Domain by Adopting Pre-trained Language Model

BioNLP@ACL, pp. 406-414, 2019.

Cited by: 0|Bibtex|Views8|DOI:https://doi.org/10.18653/v1/w19-5043
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

While deep learning techniques have shown promising results in many natural language processing (NLP) tasks, it has not been widely applied to the clinical domain. The lack of large datasets and the pervasive use of domain-specific language (i.e. abbreviations and acronyms) in the clinical domain causes slower progress in NLP tasks than...More

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