Guides: AI and Text Mining for Searching and Screening the Literature: PubMed PubReMiner

PubMed PubReMiner

PubMed PubReMiner
Allows you to directly enter, for example, a set of relevant PMIDs and determine high frequency words and subject headings associated with those specific records. Can also be used to determine the most prolific authors on a topic (based on indexed content), for example, authors who have the highest frequency of publications including a specific term like "hospital at home"[tiab]

Ways to use PubReMiner

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:

33632806 33875537 33653751 32722775 33565665 33850007 33504582 33533278 33713411 33868903 33476232 33504583

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.