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BMCBI
2008

Assessment of disease named entity recognition on a corpus of annotated sentences

8 years 9 months ago
Assessment of disease named entity recognition on a corpus of annotated sentences
Background: In recent years, the recognition of semantic types from the biomedical scientific literature has been focused on named entities like protein and gene names (PGNs) and gene ontology terms (GO terms). Other semantic types like diseases have not received the same level of attention. Different solutions have been proposed to identify disease named entities in the scientific literature. While matching the terminology with language patterns suffers from low recall (e.g., Whatizit) other solutions make use of morpho-syntactic features to better cover the full scope of terminological variability (e.g., MetaMap). Currently, MetaMap that is provided from the National Library of Medicine (NLM) is the state of the art solution for the annotation of concepts from UMLS (Unified Medical Language System) in the literature. Nonetheless, its performance has not yet been assessed on an annotated corpus. In addition, little effort has been invested so far to generate an annotated dataset that...
Antonio Jimeno-Yepes, Ernesto Jiménez-Ruiz,
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2008
Where BMCBI
Authors Antonio Jimeno-Yepes, Ernesto Jiménez-Ruiz, Vivian Lee, Sylvain Gaudan, Rafael Berlanga Llavori, Dietrich Rebholz-Schuhmann
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