Paper: UWM: Disorder Mention Extraction from Clinical Text Using CRFs and Normalization Using Learned Edit Distance Patterns

ACL ID S14-2147
Title UWM: Disorder Mention Extraction from Clinical Text Using CRFs and Normalization Using Learned Edit Distance Patterns
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

This paper describes Team UWM?s sys- tem for the Task 7 of SemEval 2014 that does disorder mention extraction and nor- malization from clinical text. For the dis- order mention extraction (Task A), the sys- tem was trained using Conditional Ran- dom Fields with features based on words, their POS tags and semantic types, as well as features based on MetaMap matches. For the disorder mention normalization (Task B), variations of disorder mentions were considered whenever exact matches were not found in the training data or in the UMLS. Suitable types of variations for disorder mentions were automatically learned using a new method based on edit distance patterns. Among nineteen partic- ipating teams, UWM ranked third in Task A with 0.755 strict F-measure and second in Task B with 0.66 strict...