↓ Skip to main content

American Association for Cancer Research

Article Metrics

Performance of Single-Nucleotide Polymorphisms in Breast Cancer Risk Prediction Models: A Systematic Review and Meta-analysis

Overview of attention for article published in Cancer Epidemiology, Biomarkers & Prevention, December 2018
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Mentioned by

twitter
2 tweeters
patent
2 patents

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
27 Mendeley
Title
Performance of Single-Nucleotide Polymorphisms in Breast Cancer Risk Prediction Models: A Systematic Review and Meta-analysis
Published in
Cancer Epidemiology, Biomarkers & Prevention, December 2018
DOI 10.1158/1055-9965.epi-18-0810
Pubmed ID
Authors

Si Ming Fung, Xin Yi Wong, Shi Xun Lee, Hui Miao, Mikael Hartman, Hwee-Lin Wee

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

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 22%
Student > Postgraduate 3 11%
Student > Master 3 11%
Student > Ph. D. Student 3 11%
Other 2 7%
Other 3 11%
Unknown 7 26%
Readers by discipline Count As %
Medicine and Dentistry 8 30%
Biochemistry, Genetics and Molecular Biology 3 11%
Agricultural and Biological Sciences 3 11%
Nursing and Health Professions 1 4%
Mathematics 1 4%
Other 3 11%
Unknown 8 30%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 16 February 2021.
All research outputs
#5,237,542
of 17,371,891 outputs
Outputs from Cancer Epidemiology, Biomarkers & Prevention
#1,524
of 3,943 outputs
Outputs of similar age
#103,956
of 275,007 outputs
Outputs of similar age from Cancer Epidemiology, Biomarkers & Prevention
#27
of 87 outputs
Altmetric has tracked 17,371,891 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 3,943 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.1. This one has gotten more attention than average, scoring higher than 60% 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 275,007 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 61% of its contemporaries.
We're also able to compare this research output to 87 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.