BARY at the NTCIR-11 MedNLP-2 Task for Complaints and Diagnosis Recognition
نویسندگان
چکیده
This paper describes a machine-learning based approach to recognizing diagnosed disease names and corresponding temporal expressions. Using CRFs (conditional random fields) to learn and predict tags, the systems described in this paper are characterized by a character-level formulation and heuristic features extracted from medical terminologies. Experimental results on the NTCIR-11 MedNLP-2 datasets suggest that the approach effectively exploit terminological resources and combine them with other NLP (natural language processing) resources including morphological analyzers.
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