Fast exact string pattern-matching algorithms adapted to the characteristics of the medical language.
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 emphasiz...
| Publicado en: | Journal of the American Medical Informatics Association Vol. 7; no. 4; pp. 378 - 392 |
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| Autores principales: | , , , |
| Formato: | research Journal Article |
| Publicado: |
Oxford University Press / USA
Jul2000
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=66282995&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 66282995 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10675027 FZ9 jtl: Journal of the American Medical Informatics Association issn: 10675027 maglogo: N pubinfo: dt: Jul2000 vid: 7 iid: 4 pid: 622 pub: Oxford University Press / USA artinfo: ui: 66282995 66282995 NLM10887166 66282995 10.1136/jamia.2000.0070378 NLM10887166 66282995 ppf: 378 ppct: 14 formats: tig: atl: Fast exact string pattern-matching algorithms adapted to the characteristics of the medical language. aug: au: Lovis, Christian Baud, Robert H Lovis, C Baud, R H affil: Affiliations of the authors: Puget Sound Health Care System, Seattle, Washington (CL); University Hospital of Geneva, Geneva, Switzerland (RHB) sug: subj: Nomenclature Algorithms Information Retrieval Methods Reproducibility of Results Validation Studies Comparative Studies Evaluation Research Multicenter Studies Clinical Assessment Tools ab: 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. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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