Document Detail


Fast exact string pattern-matching algorithms adapted to the characteristics of the medical language.
MedLine Citation:
PMID:  10887166     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
OBJECTIVE: The authors consider the problem of exact string pattern matching using algorithms that do not require any preprocessing. To choose the most appropriate algorithm, distinctive features of the medical language must be taken into account. The characteristics of medical language are emphasized in this regard, the best algorithm of those reviewed is proposed, and detailed evaluations of time complexity for processing medical texts are provided.
DESIGN: The authors first illustrate and discuss the techniques of various string pattern-matching algorithms. Next, the source code and the behavior of representative exact string pattern-matching algorithms are presented in a comprehensive manner to promote their implementation. Detailed explanations of the use of various techniques to improve performance are given.
MEASUREMENTS: Real-time measures of time complexity with English medical texts are presented. They lead to results distinct from those found in the computer science literature, which are typically computed with normally distributed texts.
RESULTS: The Boyer-Moore-Horspool algorithm achieves the best overall results when used with medical texts. This algorithm usually performs at least twice as fast as the other algorithms tested.
CONCLUSION: The time performance of exact string pattern matching can be greatly improved if an efficient algorithm is used. Considering the growing amount of text handled in the electronic patient record, it is worth implementing this efficient algorithm.
Authors:
C Lovis; R H Baud
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Journal of the American Medical Informatics Association : JAMIA     Volume:  7     ISSN:  1067-5027     ISO Abbreviation:  J Am Med Inform Assoc     Publication Date:    2000 Jul-Aug
Date Detail:
Created Date:  2000-08-15     Completed Date:  2000-08-15     Revised Date:  2013-04-17    
Medline Journal Info:
Nlm Unique ID:  9430800     Medline TA:  J Am Med Inform Assoc     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  378-91     Citation Subset:  IM    
Affiliation:
Puget Sound Health Care System, Seattle, Washington, USA. christian.lovis@dim.hcuge.ch
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Information Storage and Retrieval / methods*
Reproducibility of Results
Terminology as Topic*
Comments/Corrections

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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