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   English Wikipedia
 
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 Can electronic search engines optimize screening of search results in systematic  reviews: an empirical study Sampson M; Barrowman NJ; Moher D; Clifford TJ; Platt RW; Morrison A; Klassen TP; Zhang LBMC Med Res Methodol  2006[Feb]; 6 (ä): 7BACKGROUND: Most electronic search efforts directed at identifying primary  studies for inclusion in systematic reviews rely on the optimal Boolean search  features of search interfaces such as DIALOG and Ovid. Our objective is to test  the ability of an Ultraseek search engine to rank MEDLINE records of the included  studies of Cochrane reviews within the top half of all the records retrieved by  the Boolean MEDLINE search used by the reviewers. METHODS: Collections were  created using the MEDLINE bibliographic records of included and excluded studies  listed in the review and all records retrieved by the MEDLINE search. Records  were converted to individual HTML files. Collections of records were indexed and  searched through a statistical search engine, Ultraseek, using review-specific  search terms. Our data sources, systematic reviews published in the Cochrane  library, were included if they reported using at least one phase of the Cochrane  Highly Sensitive Search Strategy (HSSS), provided citations for both included and  excluded studies and conducted a meta-analysis using a binary outcome measure.  Reviews were selected if they yielded between 1000-6000 records when the MEDLINE  search strategy was replicated. RESULTS: Nine Cochrane reviews were included.  Included studies within the Cochrane reviews were found within the first 500  retrieved studies more often than would be expected by chance. Across all  reviews, recall of included studies into the top 500 was 0.70. There was no  statistically significant difference in ranking when comparing included studies  with just the subset of excluded studies listed as excluded in the published  review. CONCLUSION: The relevance ranking provided by the search engine was  better than expected by chance and shows promise for the preliminary evaluation  of large results from Boolean searches. A statistical search engine does not  appear to be able to make fine discriminations concerning the relevance of  bibliographic records that have been pre-screened by systematic reviewers.|*Bibliometrics[MESH]|*Meta-Analysis as Topic[MESH]|*Software[MESH]|*User-Computer Interface[MESH]|Abstracting and Indexing[MESH]|Efficiency[MESH]|Empirical Research[MESH]|Humans[MESH]|Information Storage and Retrieval/classification/*methods[MESH]|MEDLINE/instrumentation/standards/*statistics & numerical data[MESH]|Medical Subject Headings[MESH]|Periodicals as Topic[MESH]|Programming Languages[MESH]|Randomized Controlled Trials as Topic[MESH]
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