A simple search with PubMed in MEDLINE, the world's largest medical database, results quite often in a listing of many articles with little precision or recall for the average user. Therefore a medico-scientific data mining web service called Meva (MEDLINE Evaluator) was developed, capable of analyzing the bibliographic fields returned by an inquiry to PubMed. Meva converts these data into a well-structured expressive result, showing a graphical condensed representation of counts and relations of the fields using histograms, correlation tables, detailed sorted lists or MeSH trees. Users can specify filters or minimal frequencies to restrict the analysis in the data mining process. MeSH codes for MeSH terms (keywords) may be listed, the output can be limited on first or last authors. Results can be delivered as HTML or in a delimited format to import into any database. This study documents development, usage and benefits of Meva.     «

A simple search with PubMed in MEDLINE, the world's largest medical database, results quite often in a listing of many articles with little precision or recall for the average user. Therefore a medico-scientific data mining web service called Meva (MEDLINE Evaluator) was developed, capable of analyzing the bibliographic fields returned by an inquiry to PubMed. Meva converts these data into a well-structured expressive result, showing a graphical condensed representation of counts and relations o...     »