Incredibly useful PubMed search tools you wish you knew earlier 

“I need to do some reading on this.”

This past week I have spent a lot of time on PubMed.  So today I’m following up from a previous post on teaching students and early career researchers more efficient strategies to search and retrieve medical/life science literature. This post will focus on a couple of overlooked tools within PubMed.  Let’s start with an overview of my PubMed search strategy*, click through the presentation below:

Incredibly useful PubMed search tools you wish you knew earlier  – Created with Haiku Deck, presentation software that inspires

A little more detail:

1  Medical Subject Heading (MeSH) terms (link)

MeSH terms are what PubMed uses to index articles, using these enables you to target your search at a chosen level of specificity, watch the video from NCBI for a thorough explanation:

Don’t forget this tool is also incredibly valuable as a glossary and thesaurus to make sure you are searching with the correct and most specific term(s).

2  Performing a clinical query (link)

This tool quickly filters your search to only the clinical literature and groups results into three different categories (clinical study, systematic reviews and medical genetics) all displayed on the same page.  The medical genetics column is especially useful in finding variations associated with a disease.  You can further target your search by selecting either etiology, diagnosis, therapy, prognosis or clinical prediction guide under ‘category’.

Using a combination of complimentary search strategies will maximise retrieval.  Always perform a standard text/key word search but then try an alternative method (including other databases such as Google Scholar that work quite differently), these will give you different top hits and articles you would have missed when solely relying on on a single search strategy.

*Note that before you do this you will need to have developed a good research question.  Break this down into concepts to help you identify starting keywords.



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