Biochemistry Publications
Improving phenotype name recognition
Document Type
Conference Proceeding
Publication Date
6-8-2011
Journal
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
6657 LNAI
First Page
246
Last Page
257
URL with Digital Object Identifier
10.1007/978-3-642-21043-3-30
Abstract
Due to the rapidly increasing amount of biomedical literature, automatic processing of biomedical papers is extremely important. Named Entity Recognition (NER) in this type of writing has several difficulties. In this paper we present a system to find phenotype names in biomedical literature. The system is based on Metamap and makes use of the UMLS Metathesaurus and the Human Phenotype Ontology. From an initial basic system that uses only these preexisting tools, five rules that capture stylistic and linguistic properties of this type of literature are proposed to enhance the performance of our NER tool. The tool is tested on a small corpus and the results (precision 97.6% and recall 88.3%) demonstrate its performance. © 2011 Springer-Verlag.