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A validated natural language processing algorithm for brain imaging phenotypes from radiology reports in UK electronic health records

Overview of attention for article published in BMC Medical Informatics and Decision Making, September 2019
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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 (97th percentile)

Mentioned by

news
1 news outlet
twitter
16 X users
facebook
1 Facebook page

Citations

dimensions_citation
28 Dimensions

Readers on

mendeley
71 Mendeley
Title
A validated natural language processing algorithm for brain imaging phenotypes from radiology reports in UK electronic health records
Published in
BMC Medical Informatics and Decision Making, September 2019
DOI 10.1186/s12911-019-0908-7
Pubmed ID
Authors

Emily Wheater, Grant Mair, Cathie Sudlow, Beatrice Alex, Claire Grover, William Whiteley

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 71 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 20%
Student > Master 7 10%
Student > Doctoral Student 7 10%
Student > Ph. D. Student 5 7%
Other 5 7%
Other 11 15%
Unknown 22 31%
Readers by discipline Count As %
Medicine and Dentistry 16 23%
Computer Science 8 11%
Neuroscience 6 8%
Biochemistry, Genetics and Molecular Biology 2 3%
Arts and Humanities 2 3%
Other 8 11%
Unknown 29 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 September 2019.
All research outputs
#1,955,398
of 25,547,904 outputs
Outputs from BMC Medical Informatics and Decision Making
#98
of 2,150 outputs
Outputs of similar age
#39,916
of 352,269 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#2
of 35 outputs
Altmetric has tracked 25,547,904 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,150 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 95% 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 352,269 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 35 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.