A pre-search estimation algorithm for MEDLINE strategies with qualifiers.

@article{citeulike:994115, abstract = {Inexperienced users of online medical databases often have difficulty formulating their queries. Systems designed to assist them usually do not estimate how effective the initial search strategy will be before performing an actual search. Consequently, the search may find an overwhelming number of citations, or retrieve nothing at all. We have developed an estimation algorithm to predict the outcome of a MEDLINE search. The portion of the algorithm described here estimates retrieval for strategies containing qualifiers. In test searches, the estimate reduced the trial-and-error of strategy formulation. However, the accuracy of the estimate fell short of expectations. Our results show that pre-search estimation for strategies with qualifiers cannot be performed effectively with only the occurrence data that is presently available. They further imply that automated search intermediaries can benefit from medical knowledge which expresses the relationships that exist between terms.}, address = {Laboratory of Computer Science, Massachusetts General Hospital, Boston.}, author = {Merz, R. B. and Cimino, C. and Barnett, G. O. and Blewett, D. R. and Gnassi, J. A. and Grundmeier, R. and Hassan, L. }, citeulike-article-id = {994115}, issn = {0195-4210}, journal = {Proc Annu Symp Comput Appl Med Care}, keywords = {medical-informatics, medline, mghlcspub}, pages = {910--914}, posted-at = {2006-12-14 06:13:24}, priority = {2}, title = {A pre-search estimation algorithm for MEDLINE strategies with qualifiers.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/7950056}, year = {1994} }

TY - JOUR ID - citeulike:994115 L3 - citeulike-article-id:994115 TI - A pre-search estimation algorithm for MEDLINE strategies with qualifiers. JF - Proc Annu Symp Comput Appl Med Care SP - 910 EP - 914 AD - Laboratory of Computer Science, Massachusetts General Hospital, Boston. SN - 0195-4210 N2 - Inexperienced users of online medical databases often have difficulty formulating their queries. Systems designed to assist them usually do not estimate how effective the initial search strategy will be before performing an actual search. Consequently, the search may find an overwhelming number of citations, or retrieve nothing at all. We have developed an estimation algorithm to predict the outcome of a MEDLINE search. The portion of the algorithm described here estimates retrieval for strategies containing qualifiers. In test searches, the estimate reduced the trial-and-error of strategy formulation. However, the accuracy of the estimate fell short of expectations. Our results show that pre-search estimation for strategies with qualifiers cannot be performed effectively with only the occurrence data that is presently available. They further imply that automated search intermediaries can benefit from medical knowledge which expresses the relationships that exist between terms. KW - medical-informatics KW - medline KW - mghlcspub AU - Merz, RB AU - Cimino, C AU - Barnett, GO AU - Blewett, DR AU - Gnassi, JA AU - Grundmeier, R AU - Hassan, L PY - 1994/// UR - http://view.ncbi.nlm.nih.gov/pubmed/7950056 ER -