Evidence map›Paper›PMID 23160414›Full record

ArticleDatabase : the journal of biological databases and curation2012

Accelerating literature curation with text-mining tools: a case study of using PubTator to curate genes in PubMed abstracts.

Chih-Hsuan Wei, Bethany R Harris, Donghui Li, Tanya Z Berardini, Eva Huala, Hung-Yu Kao, Zhiyong Lu

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.

0numbers the graph read from it
0cells of the map it votes in
55citing 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

55 citing papers in PubMed.

  1. Article
  2. Towards discovery: an end-to-end system for uncovering novel biomedical relations.Database : the journal of biological databases and curation · 2024
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
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  10. Acronyms and Opportunities for Improving Deep Nets.Frontiers in artificial intelligence · 2021
    Article
  11. Review
  12. Article
  13. Article
  14. RCorp: a resource for chemical disease semantic extraction in Chinese.BMC medical informatics and decision making · 2019
    Article
  15. Article
  16. Article
  17. Article
  18. Global trends in infectious diseases of swine.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Review
  19. Article
  20. 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

7 authors.

Chih-Hsuan WeiNational Center for Biotechnology Information-NCBI, National Library of Medicine-NLM, 8600 Rockville Pike, Bethesda, MD 20894, USA.
Bethany R Harris
Donghui Li
Tanya Z Berardini
Eva Huala
Hung-Yu Kao
Zhiyong Lu

Funding

Named Entity Recognition and Relationship Extraction in BiomedicineZIALM091813 · NLM · NATIONAL LIBRARY OF MEDICINE · PI LU, ZHIYONG · 2013 to 2022
$13.4M
Intramural NIH HHS
6 · The paper itself

Abstract

Today's biomedical research has become heavily dependent on access to the biological knowledge encoded in expert curated biological databases. As the volume of biological literature grows rapidly, it becomes increasingly difficult for biocurators to keep up with the literature because manual curation is an expensive and time-consuming endeavour. Past research has suggested that computer-assisted curation can improve efficiency, but few text-mining systems have been formally evaluated in this regard. Through participation in the interactive text-mining track of the BioCreative 2012 workshop, we developed PubTator, a PubMed-like system that assists with two specific human curation tasks: document triage and bioconcept annotation. On the basis of evaluation results from two external user groups, we find that the accuracy of PubTator-assisted curation is comparable with that of manual curation and that PubTator can significantly increase human curatorial speed. These encouraging findings warrant further investigation with a larger number of publications to be annotated. Database URL: http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/PubTator/

Indexed as

Abstracting and IndexingDatabases, FactualGenesPeriodicals as TopicPubMedUser-Computer InterfaceData MiningFeedbackHumans

Identifiers

PMID23160414
PMCPMC3500520

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.