Abstract:Abstract. In this paper, we tackle the issue of symptom recognition for rare diseases in biomedical texts. Symptoms typically have more complex and ambiguous structure than other biomedical named entities. Furthermore, existing resources are scarce and incomplete. Therefore, we propose a weakly-supervised framework based on a combination of two approaches: sequential pattern mining under constraints and sequence labeling. We use unannotated biomedical paper abstracts with dictionaries of rare diseases and symp… Show more
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