MLTrends: Graphing MEDLINE term usage over time

Authors

  • Gareth A Palidwor Ottawa Hospital Research Institute
  • Miguel A Andrade-Navarro Max Delbrück Center for Molecular Medicine

DOI:

https://doi.org/10.5210/disco.v5i0.2680

Abstract

The MEDLINE database of medical literature is routinely used by researchers and doctors to find articles pertaining to their area of interest. Insight into historical changes in research areas and use of scientific language may be gained by chronological analysis of the 18 million records currently in the database, however such analysis is generally complex and time consuming. The authors’ MLTrends web application graphs term usage in MEDLINE over time, allowing the determination of emergence dates for biomedical terms and historical variations in term usage intensity. Terms considered are individual words or quoted phrases which may be combined using Boolean operators. MLTrends can plot the number of records in MEDLINE per year whose titles or abstracts match each queried term for multiple terms simultaneously. The MEDLINE database is stored and indexed on the MLTrends server allowing queries to be completed and graphs generated in less than one second. Queries may be performed on all titles and/or abstracts in MEDLINE and can include stop words. The resulting graphs may be normalized by total publications or words per year to facilitate term usage comparison between years. This makes MLTrends a powerful tool for rapid evaluation of the evolution of biomedical research and language in a graphical way. MLTrends may be used at: http://www.ogic.ca/mltrends

Author Biographies

Gareth A Palidwor, Ottawa Hospital Research Institute

Gareth Palidwor Bioinformatics Software Developer

Miguel A Andrade-Navarro, Max Delbrück Center for Molecular Medicine

Group leader of the Computational Biology and Data Mining group at the Max Delbrück Center for Molecular Medicine

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Published

2010-01-22

How to Cite

Palidwor, G. A., & Andrade-Navarro, M. A. (2010). MLTrends: Graphing MEDLINE term usage over time. DISCO: Journal of Biomedical Discovery and Collaboration, 5, 1–6. https://doi.org/10.5210/disco.v5i0.2680

Issue

Section

Articles