Text mining for searching and screening the literature
This guide is intended to provide an overview of the definition and application of text mining in search strategy development and study selection; it includes a list of tools and resources that librarians or other motivated searchers may wish to try
Allows you to directly enter, for example, a set of relevant PMIDs and determine high frequency words and subject headings assigned to those specific records, and can also be used to determine the most prolific authors on a topic, for example, authors who have the highest frequency of publications including the term hospital at home[tiab]
In this example related to building a search strategy to identify studies on regulatory strategies for the prevention of vaping in youth, I am using the following records to identify words, MeSH terms, and subheadings to add to a search strategy:
I pulled this list of accession numbers for PubMed records (PMIDs, also called unique identifiers in Ovid MEDLINE) from relevant records identified by the research team: These records should refer to studies the researcher would consider for inclusion in a review
Based on these results, I might consider adding the subheading "legislation and jurisprudence"[subheading] in PubMed (or lj.fs. in Ovid MEDLINE) to a search strategy seeking articles on the effects of regulations on vaping in youth, for example.