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A modular framework for biomedical concept recognition

Overview of attention for article published in BMC Bioinformatics, September 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)

Mentioned by

twitter
10 tweeters
googleplus
1 Google+ user

Citations

dimensions_citation
41 Dimensions

Readers on

mendeley
79 Mendeley
citeulike
4 CiteULike
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Title
A modular framework for biomedical concept recognition
Published in
BMC Bioinformatics, September 2013
DOI 10.1186/1471-2105-14-281
Pubmed ID
Authors

David Campos, Sérgio Matos, José Luís Oliveira

Abstract

Concept recognition is an essential task in biomedical information extraction, presenting several complex and unsolved challenges. The development of such solutions is typically performed in an ad-hoc manner or using general information extraction frameworks, which are not optimized for the biomedical domain and normally require the integration of complex external libraries and/or the development of custom tools.

Twitter Demographics

The data shown below were collected from the profiles of 10 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Brazil 2 3%
Switzerland 1 1%
Netherlands 1 1%
Australia 1 1%
Colombia 1 1%
Iran, Islamic Republic of 1 1%
Mexico 1 1%
Russia 1 1%
Other 2 3%
Unknown 66 84%

Demographic breakdown

Readers by professional status Count As %
Student > Master 21 27%
Researcher 18 23%
Student > Ph. D. Student 16 20%
Professor 5 6%
Student > Bachelor 4 5%
Other 12 15%
Unknown 3 4%
Readers by discipline Count As %
Computer Science 40 51%
Agricultural and Biological Sciences 10 13%
Biochemistry, Genetics and Molecular Biology 5 6%
Engineering 4 5%
Linguistics 3 4%
Other 10 13%
Unknown 7 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 November 2013.
All research outputs
#1,489,772
of 12,732,596 outputs
Outputs from BMC Bioinformatics
#631
of 4,738 outputs
Outputs of similar age
#21,304
of 161,517 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 1 outputs
Altmetric has tracked 12,732,596 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,738 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 161,517 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them