Paper: TMUNSW: Disorder Concept Recognition and Normalization in Clinical Notes for SemEval-2014 Task 7

ACL ID S14-2118
Title TMUNSW: Disorder Concept Recognition and Normalization in Clinical Notes for SemEval-2014 Task 7
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

We present our participation in Task 7 of SemEval shared task 2014. The goal of this particular task includes the identifica- tion of disorder named entities and the mapping of each disorder to a unique Uni- fied Medical Language System concept identifier, which were referred to as Task A and Task B respectively. We partici- pated in both of these subtasks and used YTEX as a baseline system. We further developed a supervised linear chain Con- ditional Random Field model based on sets of features to predict disorder men- tions. To take benefit of results from both systems we merged these results. Under strict condition our best run evaluated at 0.549 F-measure for Task A and an accu- racy of 0.489 for Task B on test dataset. Based on our error analysis we conclude that recall ...