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Identifying patients with suspected lung cancer in primary care: derivation and validation of an algorithm

Overview of attention for article published in British Journal of General Practice, November 2011
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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 (90th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

news
1 news outlet
twitter
5 X users

Citations

dimensions_citation
85 Dimensions

Readers on

mendeley
117 Mendeley
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Title
Identifying patients with suspected lung cancer in primary care: derivation and validation of an algorithm
Published in
British Journal of General Practice, November 2011
DOI 10.3399/bjgp11x606627
Pubmed ID
Authors

Julia Hippisley-Cox, Carol Coupland

Abstract

Lung cancer has one of the lowest survival outcomes of any cancer because more then two-thirds of patients are diagnosed when curative treatment is not possible. The challenge is to help earlier diagnosis of lung cancer and hence improve prognosis.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 117 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Unknown 116 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 23 20%
Student > Ph. D. Student 21 18%
Other 14 12%
Student > Bachelor 10 9%
Student > Master 10 9%
Other 15 13%
Unknown 24 21%
Readers by discipline Count As %
Medicine and Dentistry 43 37%
Nursing and Health Professions 6 5%
Biochemistry, Genetics and Molecular Biology 4 3%
Computer Science 3 3%
Immunology and Microbiology 3 3%
Other 19 16%
Unknown 39 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 28 September 2019.
All research outputs
#2,452,427
of 23,418,312 outputs
Outputs from British Journal of General Practice
#1,163
of 4,359 outputs
Outputs of similar age
#13,174
of 143,251 outputs
Outputs of similar age from British Journal of General Practice
#3
of 35 outputs
Altmetric has tracked 23,418,312 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 4,359 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.3. This one has gotten more attention than average, scoring higher than 73% 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 143,251 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% 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 94% of its contemporaries.