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Automated identification of pneumonia in chest radiograph reports in critically ill patients

Overview of attention for article published in BMC Medical Informatics and Decision Making, August 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 (88th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

news
1 news outlet
twitter
2 tweeters

Citations

dimensions_citation
23 Dimensions

Readers on

mendeley
63 Mendeley
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Title
Automated identification of pneumonia in chest radiograph reports in critically ill patients
Published in
BMC Medical Informatics and Decision Making, August 2013
DOI 10.1186/1472-6947-13-90
Pubmed ID
Authors

Vincent Liu, Mark P Clark, Mark Mendoza, Ramin Saket, Marla N Gardner, Benjamin J Turk, Gabriel J Escobar

Abstract

Prior studies demonstrate the suitability of natural language processing (NLP) for identifying pneumonia in chest radiograph (CXR) reports, however, few evaluate this approach in intensive care unit (ICU) patients.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 6%
United Kingdom 3 5%
Spain 1 2%
Unknown 55 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 16%
Student > Postgraduate 8 13%
Student > Master 8 13%
Student > Bachelor 7 11%
Student > Ph. D. Student 7 11%
Other 13 21%
Unknown 10 16%
Readers by discipline Count As %
Medicine and Dentistry 25 40%
Computer Science 12 19%
Nursing and Health Professions 3 5%
Engineering 3 5%
Psychology 2 3%
Other 6 10%
Unknown 12 19%

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 17 June 2017.
All research outputs
#1,113,418
of 11,374,668 outputs
Outputs from BMC Medical Informatics and Decision Making
#109
of 1,050 outputs
Outputs of similar age
#14,180
of 126,214 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#4
of 31 outputs
Altmetric has tracked 11,374,668 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,050 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 89% 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 126,214 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 88% of its contemporaries.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.