| Using rule-based natural language processing to improve disease normalization in biomedical text. | |
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MedLine Citation:
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PMID: 23043124 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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BACKGROUND AND OBJECTIVE: In order for computers to extract useful information from unstructured text, a concept normalization system is needed to link relevant concepts in a text to sources that contain further information about the concept. Popular concept normalization tools in the biomedical field are dictionary-based. In this study we investigate the usefulness of natural language processing (NLP) as an adjunct to dictionary-based concept normalization. METHODS: We compared the performance of two biomedical concept normalization systems, MetaMap and Peregrine, on the Arizona Disease Corpus, with and without the use of a rule-based NLP module. Performance was assessed for exact and inexact boundary matching of the system annotations with those of the gold standard and for concept identifier matching. RESULTS: Without the NLP module, MetaMap and Peregrine attained F-scores of 61.0% and 63.9%, respectively, for exact boundary matching, and 55.1% and 56.9% for concept identifier matching. With the aid of the NLP module, the F-scores of MetaMap and Peregrine improved to 73.3% and 78.0% for boundary matching, and to 66.2% and 69.8% for concept identifier matching. For inexact boundary matching, performances further increased to 85.5% and 85.4%, and to 73.6% and 73.3% for concept identifier matching. CONCLUSIONS: We have shown the added value of NLP for the recognition and normalization of diseases with MetaMap and Peregrine. The NLP module is general and can be applied in combination with any concept normalization system. Whether its use for concept types other than disease is equally advantageous remains to be investigated. |
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Authors:
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Ning Kang; Bharat Singh; Zubair Afzal; Erik M van Mulligen; Jan A Kors |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2012-10-6 |
Journal Detail:
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Title: Journal of the American Medical Informatics Association : JAMIA Volume: - ISSN: 1527-974X ISO Abbreviation: J Am Med Inform Assoc Publication Date: 2012 Oct |
Date Detail:
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Created Date: 2012-10-8 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9430800 Medline TA: J Am Med Inform Assoc Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
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Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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