Abstract
Although there are many clinical and biomedical language models for the English language, there is still a significant lack of models for Spanish. In this presentation, we introduce Clinical Flair, the first Spanish language model trained on real diagnoses from the Chilean public healthcare system. Taking the Named Entity Recognition task as a case study, we show that contextualized embeddings retrieved from our domain-specific language model outperform the results of the general domain model by a wide margin. In addition, we show that training a language model on real diagnoses may be more beneficial than training on electronic health records.
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