| Domain-specific analytical language modeling--the chief complaint as a case study. | |
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MedLine Citation:
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PMID: 19307149 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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PURPOSE: A large share of the information in electronic medical records (EMRs) consists of free-text compositions. From a computational point-of-view, the continuing prevalence of free-text entry is a major hindrance when the goal is to increase automation in EMRs. However, the efforts in developing standards for the structured representation of medical information have not proven to be a panacea. The information space of clinical medicine is very diverse and constantly evolving, making it challenging to develop standards for the domain. This paper reports a study aiming to increase automation in the EMR through the computational understanding of specific class of medical text in English, namely emergency department chief complaints. METHODS: We apply domain-specific analytical modeling for the computational understanding of chief complaints. We evaluate the performance of this approach in the automatic classification of chief complaints, e.g., for use in automatic syndromic surveillance. RESULTS: The evaluation in a multi-hospital setting showed that the presented algorithm was accurate in terms of classification correctness. Also, use of approximate matching in the algorithm to cope with typographic variance did not affect classification correctness while increasing classification completeness. |
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Authors:
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Jari Yli-Hietanen; Samuli Niiranen; Michael Aswell; Larry Nathanson |
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Publication Detail:
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Type: Journal Article Date: 2009-03-23 |
Journal Detail:
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Title: International journal of medical informatics Volume: 78 ISSN: 1872-8243 ISO Abbreviation: Int J Med Inform Publication Date: 2009 Dec |
Date Detail:
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Created Date: 2009-11-05 Completed Date: 2010-01-26 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9711057 Medline TA: Int J Med Inform Country: Ireland |
Other Details:
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Languages: eng Pagination: e27-30 Citation Subset: IM |
Affiliation:
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Department of Signal Processing, Tampere University of Technology, Tampere, Finland. jari.yli-hietanen@tut.fi |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms Electronic Health Records* Hospital Information Systems Humans Medical Records Systems, Computerized* Natural Language Processing* Vocabulary, Controlled* |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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