A (really good) Idea for a 3rd Party PubMed/MEDLINE Tool

Rachel Walden writes:

What I’d like to do is to be able to enter the PMIDs of several citations and have the tool search MEDLINE via PubMed for the assigned MeSH terms, and return a single list of the terms used by any of the entered citations with a measurement of frequency. For example, if I input PMIDs 16234728, 15674923, and 17443536, the tool would return results telling me that 100% or 3 of 3 use the term “Catheters, Indwelling”, 2 of 3 use “Time Factors,” 1 of the 3 uses “Urination Disorders,” and so on. Although this example uses 3 PMIDs, I’d like to be able to input at least 10, just based on personal experience.

This would be useful in situations where a single “gold standard” search strategy is needed for the purposes of a systematic review or other process – for example, we may find a number of great articles on a topic by using multiple approaches to the search, but have difficulty developing a single strategy that captures them all due to differences in indexing. In effect, it would inform reverse-engineering a search strategy from a pool of relevant citations. It might also be helpful as a teaching tool for medical librarianship students and those new to the profession.

No, it wouldn’t change my medical librarian life, but it would make it easier from time to time!

This is a really great idea and I don’t think it’d be too difficult to implement for a Web applications developer who knows how to work with NCBI’s API tools. Any takers? – David

24 thoughts on “A (really good) Idea for a 3rd Party PubMed/MEDLINE Tool

  1. Thanks for posting this, David. Now, if anybody can do this and would like an additional challenge, detecting keyword phrases might also be handy. 😉

  2. That would be an outstanding tool! I create a lot of complex search hedges, and it takes a lot of time to do manually, backing and forthing. It wouldn’t replace it entirely, but such a tool would make it a lot more coherent. It would also be helpful for novice or sometime searchers.

  3. We have medline in our own index and this is possible with facets.

    So, for a query “pmid:15738026 OR pmid:16190103 OR pmid:15982726” you would get these mesh (includes minor and major but can be separated) terms:

    “Humans” 3
    “Female” 2
    “diagnosis” 2
    “Adult” 1
    “Aged” 1
    “Cervical Intraepithelial Neoplasia” 1

    it is also possible for keywords and just about any field including substance:

    “Insulin-Like Growth Factor Binding Protein 3” 1
    “Insulin-Like Growth Factor II” 1
    “Tumor Markers, Biological” 1
    “Vascular Endothelial Growth Factor B” 1
    “Vascular Endothelial Growth Factor C” 1

    or journal:

    “Gynecologic oncology” 1
    “Obstetrics and gynecology” 1
    “The Malaysian journal of pathology” 1

    It can get interesting when you search on more general topics and see which Affiliations, Authors, Journals, and so forth have highest counts.

  4. Martin, I just tried yours out and it looks like you almost got it working. I see what you mean about the counts, though, and I’m seeing some discrepancies in the terms retrieved, too (Are you using the Muenchian method for the grouping, or are you handling this another way? Just curious). Great start, though! I think you are also right about gopubmed. I gave it a shot and it seemed to do the job beautifully. Doesn’t calculate percentages, but it does tally and give a nice visual to indicate frequency. For others that are interested in this, give gopubmed a try.

    1)Go to: http://www.gopubmed.com
    2)Paste this list of 10 pmids into the box and click find it:
    18476325 17946774 17411327 17312256 17254294 17236650 17217501 17178562 17142816 17124781
    observe the wonders of the ‘Top Categories’ on the left, including counts for matches in MeSH and Gene Ontologies.


  5. Gopubmed does work nicely for this. The MeSH terms from the set entered are displayed in the left col under Top Categories in a hierarchy which allows you to expand the search to a higher level category than the MeSH terms returned. But if you were using this just to get a deduped set of MeSH terms for the PMIDs entered and ordered, you’d have to navigate the tree to find the terms, .e.g in the above set of PMIDs Genetic Predisposition to Disease is a term is in the set, but falls under Techniques and Equipment in this interface. I haven’t spent too much time with gopubmed so may not be fully understanding this.

    I had some code doing a similar thing and modified it for this purpose.


  6. Rachel, sorry about the confusion. Facets will be in a later release – it is not at pubget yet. I was just suggesting that as a possible technical solution to the problem.

  7. Hi David,

    about your comment "e.g. in the above set of PMIDs Genetic Predisposition to Disease is a term is in the set, but falls under Techniques and Equipment in this interface."

    As you know "MeSH consists of sets of terms naming descriptors in a hierarchical structure that permits searching at various levels of specificity" and in case of "Genetic Predisposition to Disease" you can find it under "Techniques and Equipment" and/or "Diseases" and/or "Biological Sciences".

    About your comment: "you’d have to navigate the tree to find the terms" yes you can navigate or you can also use "Find related categories" and/or use advanced search.

    Best regards,

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  9. Hi David and company! Thank you for sharing your knowledge. I’ve been trying gopubmed and I post it on my library blog.

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