Evidence map›Paper›PMID 26958181›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium

Extracting Characteristics of the Study Subjects from Full-Text Articles.

Dina Demner-Fushman, James G Mork

Abstract read
PubMed Full text at PMC
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

2 authors.

Dina Demner-FushmanNational Library of Medicine, National Institutes of Health, HHS Bethesda, MD, USA.
James G MorkNational Library of Medicine, National Institutes of Health, HHS Bethesda, MD, USA.

Funding

Semantic indexing of biomedical publications and clinical textZIALM010005 · NLM · NATIONAL LIBRARY OF MEDICINE · PI DEMNER-FUSHMAN, DINA · 2016 to 2020
$4.0M
6 · The paper itself

Abstract

Characteristics of the subjects of biomedical research are important in determining if a publication describing the research is relevant to a search. To facilitate finding relevant publications, MEDLINE citations provide Medical Subject Headings that describe the subjects' characteristics, such as their species, gender, and age. We seek to improve the recommendation of these headings by the Medical Text Indexer (MTI) that supports manual indexing of MEDLINE. To that end, we explore the potential of the full text of the publications. Using simple recall-oriented rule-based methods we determined that adding sentences extracted from the methods sections and captions to the abstracts prior to MTI processing significantly improved recall and F1 score with only a slight drop in precision. Improvements were also achieved in directly assigning several headings extracted from the full text. These results indicate the need for further development of automated methods capable of leveraging the full text for indexing.

Indexed as

Data MiningDemographyResearch SubjectsAbstracting and IndexingAlgorithmsAnimalsBiomedical ResearchHumansInformation Storage and RetrievalMEDLINE

Identifiers

PMID26958181
PMCPMC4765643

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.