Evidence map›Paper›PMID 30417176›Full record

ArticleProceedings of the 1st Workshop on Scholarly Web Mining. Workshop on Scholarly Web Mining (1st : 2017 : Cambridge, England)2017

Predicting MeSH Beyond MEDLINE.

Adam K Kehoe, Vetle I Torvik, Matthew B Ross, Neil R Smalheiser

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings of the 1st Workshop on Scholarly Web Mining. Workshop on Scholarly Web Mining (1st : 2017 : Cambridge, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

4 authors.

Adam K KehoeSchool of Information Sciences, University of Illinois at Urbana-Champaign, Champaign, IL.
Vetle I TorvikSchool of Information Sciences, University of Illinois at Urbana-Champaign, Champaign, IL.
Matthew B RossDepartment of Economics, Ohio State University, Columbus, OH.
Neil R SmalheiserDepartment of Psychiatry, University of Illinois at Chicago, Chicago, IL.

Funding

LIFE CYCLE EVENTS, PRODUCTIVITY, AND SCIENTIFIC IMPACTP01AG039347 · NIA · NATIONAL BUREAU OF ECONOMIC RESEARCH · PI BHATTACHARYA, JAY · 2013 to 2018
$5.4M
Text Mining Pipeline to Accelerate Systematic Reviews in Evidence-Based MedicineR01LM010817 · NLM · UNIVERSITY OF ILLINOIS AT CHICAGO · PI COHEN, AARON M., SMALHEISER, NEIL R · 2010 to 2019
$4.5M
NIA NIH HHS P01 AG039347NLM NIH HHS R01 LM010817
6 · The paper itself

Abstract

Medical subject headings (MeSH) are a flexible and useful tool for describing biomedical concepts. Here, we present MeSHier, a tool for assigning MeSH terms to biomedical documents based on abstract similarity and references to MEDLINE records. When applied to PubMedCentral papers, NIH grants, and USPTO patents we find that these two sources of information produce largely disjoint sets of related MEDLINE records, albeit with some overlap in MeSH. When combined they provide an enriched topical annotation that would not have been possible with either alone. MeSHier is available as a demo tool that can take as input IDs of PubMed papers, USPTO patents, and NIH grants: http://abel.lis.illinois.edu/cgi-bin/meshier/search.py.

Indexed as

Controlled vocabulariesMedical subject headings

Identifiers

PMID30417176
PMCPMC6221467

What OpenQuestion holds

Textmetadata
LicenceTDM
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.