Identifying and classifying semantic relations between medical concepts in clinical data (I2b2 Challenge)
نویسنده
چکیده
In this paper, we describe the three system runs that we submitted to the I2B2-10 Shared Task Challenges in Natural Language Processing and Clinical Data. We participated in the relation identification track of the competition. Our models use a combination of lexical representation, medical semantic information, and additional contextual knowledge in combination with SVM classification algorithms. The best results on the test set are obtained by a 9-class classification algorithm using all types of features as representation technique.
منابع مشابه
Linguistic and semantic annotation for information extraction and characterization
The 2010 I2B2 NLP challenge concentrated on extraction of three types of information from clinical records: medical concepts, their certainty status and relations between them. For participation in this challenge, we designed an automatic NLP system exploiting terminological resources and a rule-based approach. An attemp was also made to apply knowledge engineering methods. Our system provides ...
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