We used MetaMap and YTEX as a basis for the construc- tion of two separate systems to participate in the 2013 ShARe/CLEF eHealth Task 1[9], the recognition of clinical concepts. No modifications were directly made to these systems, but output concepts were filtered using stop concepts, stop concept text and UMLS semantic type. Con- cept boundaries were also adjusted using a small collection of rules to increase precision on the strict task. Overall MetaMap had better per- formance than YTEX on the strict task, primarily due to a 20% perfor- mance improvement in precision. In the relaxed task YTEX had better performance in both precision and recall giving it an overall F-Score 4.6% higher than MetaMap on the test data. Our results also indicated a 1.3% higher accuracy for YTEX in UMLS CUI mapping.
@article{arxiv.1402.1668,
title = {Evaluation of YTEX and MetaMap for clinical concept recognition},
author = {John David Osborne and Binod Gyawali and Thamar Solorio},
journal= {arXiv preprint arXiv:1402.1668},
year = {2014}
}
Comments
6 pages, working notes to the ShareClef eHealth 2013 Shared Task