| Applying natural language processing toolkits to electronic health records - an experience report. | |
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MedLine Citation:
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PMID: 19380974 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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A natural language challenge devised by Informatics for Integrating Biology and the Bedside (i2b2) was to analyze free-text health data to construct a multi-class, multi-label classification system focused on obesity and its co-morbidities. This report presents a case study in which a natural language processing (NLP) toolkit, called NLTK, was used in the challenge. This report provides a brief review of NLP in the context of EHR applications, briefly surveys and contrasts some existing NLP toolkits, and reports on our experiences with the i2b2 case study. Our efforts uncovered issues including the lack of human annotated physician notes for use as NLP training data, differences between conventional free-text and medical notes, and potential hardware and software limitations affecting future projects. |
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Authors:
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Neil Barrett; Jens H Weber-Jahnke |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: Studies in health technology and informatics Volume: 143 ISSN: 0926-9630 ISO Abbreviation: Stud Health Technol Inform Publication Date: 2009 |
Date Detail:
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Created Date: 2009-04-21 Completed Date: 2009-06-18 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9214582 Medline TA: Stud Health Technol Inform Country: Netherlands |
Other Details:
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Languages: eng Pagination: 441-6 Citation Subset: T |
Affiliation:
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Department of Computer Science, University of Victoria, Victoria, BC, Canada. nbarrett@uvic.ca |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Medical Records Systems, Computerized
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organization & administration* Natural Language Processing* |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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