ArticleJAMIA open2018
Understanding the research landscape of major depressive disorder via literature mining: an entity-level analysis of PubMed data from 1948 to 2017.
Article in JAMIA open, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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.
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Who cites it
0 citing papers in PubMed, 7 citations in OpenAlex.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo analyze literature-based data from PubMed to identify diseases and medications that have frequently been studied with major depressive disorder (MDD). MATERIALS AND
methodsAbstracts of 23 799 research articles about MDD that have been published since 1948 till 2017 were analyzed using data and text mining approaches. Methods such as information extraction, frequent pattern mining, regression, and burst detection were used to explore diseases and medications that have been associated with MDD.
resultsIn addition to many mental disorders and antidepressants, we identified several nonmental health diseases and nonpsychotropic medications that have frequently been studied with MDD. Our results suggest that: (1) MDD has been studied with disorders such as DISCUSSION AND
conclusionThis study summarized and presented an overview of the previous MDD research in terms of diseases and medications that are highly relevant to MDD. The reported results can potentially facilitate hypothesis generation for future studies. The approaches proposed in the study can be used to better understand the progress and advance of the field.
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Registered trials
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.