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Natural language processing for disease phenotyping in UK primary care records for research: a pilot study in myocardial infarction and death

Overview of attention for article published in Journal of Biomedical Semantics, November 2019
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

twitter
10 tweeters

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
44 Mendeley
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Title
Natural language processing for disease phenotyping in UK primary care records for research: a pilot study in myocardial infarction and death
Published in
Journal of Biomedical Semantics, November 2019
DOI 10.1186/s13326-019-0214-4
Pubmed ID
Authors

Anoop D. Shah, Emily Bailey, Tim Williams, Spiros Denaxas, Richard Dobson, Harry Hemingway

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 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 14%
Student > Ph. D. Student 5 11%
Researcher 4 9%
Professor 3 7%
Student > Bachelor 3 7%
Other 9 20%
Unknown 14 32%
Readers by discipline Count As %
Computer Science 6 14%
Medicine and Dentistry 6 14%
Nursing and Health Professions 3 7%
Engineering 2 5%
Psychology 2 5%
Other 8 18%
Unknown 17 39%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 22 November 2019.
All research outputs
#4,649,448
of 17,415,680 outputs
Outputs from Journal of Biomedical Semantics
#108
of 356 outputs
Outputs of similar age
#110,052
of 331,804 outputs
Outputs of similar age from Journal of Biomedical Semantics
#4
of 19 outputs
Altmetric has tracked 17,415,680 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 356 research outputs from this source. They receive a mean Attention Score of 4.5. This one has gotten more attention than average, scoring higher than 69% 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 331,804 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.