Evidence map›Paper›PMID 30329013›Full record

ArticleBioinformatics (Oxford, England)2019

Thalia: semantic search engine for biomedical abstracts.

Axel J Soto, Piotr Przybyła, Sophia Ananiadou

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
–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

19 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Big Data and Atrial Fibrillation: Current Understanding and New Opportunities.Journal of cardiovascular translational research · 2020
    Review
  14. Women's health inBMJ open · 2020
    Observational
  15. Article
  16. Improving reference prioritisation with PICO recognition.BMC medical informatics and decision making · 2019
    Article
  17. Article
  18. Article
  19. 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

3 authors.

Axel J SotoNational Centre for Text Mining, School of Computer Science, University of Manchester, Manchester, UK.
Piotr PrzybyłaNational Centre for Text Mining, School of Computer Science, University of Manchester, Manchester, UK.
Sophia AnaniadouNational Centre for Text Mining, School of Computer Science, University of Manchester, Manchester, UK.

Funding

Biotechnology and Biological Sciences Research Council BB/M006891/1Medical Research Council MR/N00583X/1
6 · The paper itself

Abstract

summaryAlthough the publication rate of the biomedical literature has been growing steadily during the last decades, the accessibility of pertinent research publications for biologist and medical practitioners remains a challenge. This article describes Thalia, which is a semantic search engine that can recognize eight different types of concepts occurring in biomedical abstracts. Thalia is available via a web-based interface or a RESTful API. A key aspect of our search engine is that it is updated from PubMed on a daily basis. We describe here the main building blocks of our tool as well as an evaluation of the retrieval capabilities of Thalia in the context of a precision medicine dataset. AVAILABILITY AND IMPLEMENTATION: Thalia is available at http://nactem.ac.uk/Thalia_BI/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Search EngineInternetPubMedSemantics

Identifiers

PMID30329013
PMCPMC6513154

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.