IHS-RD-Belarus: Identification and Normalization of Disorder Concepts in Clinical Notes

摘要

This paper describes clinical disorder recognition and encoding system submitted by IHS R&D Belarus team at the SemEval-2015 shared task related to analysis of clinical texts. Our system is based on IHS Goldfire Linguistic Processor and uses a rich set of lexical, syntactic and semantic features. The proposed system consists of two components: a CRF-based approach to recognize disorder entities and empirical ranking to encode disorders to UMLS CUIs. Evaluation on the test data set showed that our system achieved the F-measure of 0.898 for entity recognition and the F-measure of 0.794 for UMLS CUI. The combined score for whole task is 0.690 (rank 17 out of 40 submissions).