Evidence map›Paper›PMID 24551329›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2013

Semantic MEDLINE for discovery browsing: using semantic predications and the literature-based discovery paradigm to elucidate a mechanism for the obesity paradox.

Michael J Cairelli, Christopher M Miller, Marcelo Fiszman, T Elizabeth Workman, Thomas C Rindflesch

Open access · greenAbstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.8field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 37 citations in OpenAlex.

  1. Drug repurposing for COVID-19 via knowledge graph completion.Journal of biomedical informatics · 2021
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  6. SemNet: Using Local Features to Navigate the Biomedical Concept Graph.Frontiers in bioengineering and biotechnology · 2019
    Article
  7. A Literature Based Discovery Visualization System with Hierarchical Clustering and Linking Set Associations.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019
    Article
  8. Article
  9. Article
  10. Rediscovering Don Swanson: the Past, Present and Future of Literature-Based Discovery.Journal of data and information science (Warsaw, Poland) · 2017
    Article
  11. Review
  12. Article
  13. Operationalizing Semantic Medline for meeting the information needs at point of care.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2015
    Article
  14. Article
  15. Article
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Michael J CairelliNational Institutes of Health, National Library of Medicine, Lister Hill National Center for Biomedical Communications, Bethesda, MD, USA.
Christopher M MillerNational Institutes of Health, National Library of Medicine, Lister Hill National Center for Biomedical Communications, Bethesda, MD, USA.
Marcelo FiszmanNational Institutes of Health, National Library of Medicine, Lister Hill National Center for Biomedical Communications, Bethesda, MD, USA.
T Elizabeth WorkmanNational Institutes of Health, National Library of Medicine, Lister Hill National Center for Biomedical Communications, Bethesda, MD, USA.
Thomas C RindfleschNational Institutes of Health, National Library of Medicine, Lister Hill National Center for Biomedical Communications, Bethesda, MD, USA.
National Center for Biotechnology Information · USNational Institutes of Health · US

Funding

Intramural NIH HHS
6 · The paper itself

Abstract

Applying the principles of literature-based discovery (LBD), we elucidate the paradox that obesity is beneficial in critical care despite contributing to disease generally. Our approach enhances a previous extension to LBD, called "discovery browsing," and is implemented using Semantic MEDLINE, which summarizes the results of a PubMed search into an interactive graph of semantic predications. The methodology allows a user to construct argumentation underpinning an answer to a biomedical question by engaging the user in an iterative process between system output and user knowledge. Components of the Semantic MEDLINE output graph identified as "interesting" by the user both contribute to subsequent searches and are constructed into a logical chain of relationships constituting an explanatory network in answer to the initial question. Based on this methodology we suggest that phthalates leached from plastic in critical care interventions activate PPAR gamma, which is anti-inflammatory and abundant in obese patients.

Indexed as

MEDLINENatural Language ProcessingObesityHumansInformation Storage and RetrievalSemantics

Identifiers

PMID24551329
PMCPMC3900170
OpenAlexW85744764

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.