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Using existing biomedical resources to detect and ground terms in biomedical literature


Kaljurand, K; Rinaldi, Fabio; Kappeler, T; Schneider, G (2009). Using existing biomedical resources to detect and ground terms in biomedical literature. In: Combi, C; Shahar, Y; Abu-Hanna, A. Artificial Intelligence in Medicine: 12th Conference on Artificial Intelligence in Medicine, AIME 2009, Verona, Italy, July 18-22, 2009. Proceedings. Berlin: Springer, 225-234.

Abstract

We present an approach towards the automatic detection of
names of proteins, genes, species, etc. in biomedical literature and their grounding to widely accepted identifiers. The annotation is based on a large term list that contains the common expression of the terms, a normalization step that matches the terms with their actual representation in the texts, and a disambiguation step that resolves the ambiguity of matched terms. We describe various characteristics of the terms found in existing term resources and of the terms that are used in biomedical texts. We evaluate our results against a corpus of manually annotated protein mentions and achieve a precision of 57% and recall of 72%.

Abstract

We present an approach towards the automatic detection of
names of proteins, genes, species, etc. in biomedical literature and their grounding to widely accepted identifiers. The annotation is based on a large term list that contains the common expression of the terms, a normalization step that matches the terms with their actual representation in the texts, and a disambiguation step that resolves the ambiguity of matched terms. We describe various characteristics of the terms found in existing term resources and of the terms that are used in biomedical texts. We evaluate our results against a corpus of manually annotated protein mentions and achieve a precision of 57% and recall of 72%.

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Additional indexing

Item Type:Book Section, refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Uncontrolled Keywords:NLP, named-entity recognition, term grounding, MINT, IntAct
Language:English
Date:22 July 2009
Deposited On:04 Feb 2010 09:08
Last Modified:15 Aug 2017 02:57
Publisher:Springer
Series Name:Springer Lecture Notes in Computer Science
Number:5651
ISBN:978-3-642-02975-2
Funders:Swiss National Science Fund, grant 100014-118396/1
Official URL:http://www.springerlink.com/content/83361721495636m2/
Related URLs:http://aimedicine.info/aime09/ (Organisation)

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