Abstract
A simple search with PubMed in MEDLINE, the world’s largest medical database, results quite often in a listing of many articles with little relevance for the 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. The user can specify filters or minimal frequencies to restrict the analysis in the data mining process. MeSH codes for MeSH terms may be listed. Furthermore he can limit the output on first authors. Results can be delivered as HTML or in a delimited format to import into any database.
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Tenner, H., Thurmayr, G.R., Thurmayr, R. (2003). Data Mining with Meva in MEDLINE. In: Perner, P., Brause, R., Holzhütter, HG. (eds) Medical Data Analysis. ISMDA 2003. Lecture Notes in Computer Science, vol 2868. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39619-2_6
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DOI: https://doi.org/10.1007/978-3-540-39619-2_6
Publisher Name: Springer, Berlin, Heidelberg
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