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Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example

Overview of attention for article published in Frontiers in Genetics, August 2014
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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 (93rd percentile)

Mentioned by

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17 X users
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1 patent

Citations

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46 Dimensions

Readers on

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96 Mendeley
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Title
Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example
Published in
Frontiers in Genetics, August 2014
DOI 10.3389/fgene.2014.00254
Pubmed ID
Authors

Benjamin A. Goldstein, Joshua W. Knowles, Elias Salfati, John P. A. Ioannidis, Themistocles L. Assimes

Abstract

Genetic risk assessment is becoming an important component of clinical decision-making. Genetic Risk Scores (GRSs) allow the composite assessment of genetic risk in complex traits. A technically and clinically pertinent question is how to most easily and effectively combine a GRS with an assessment of clinical risk derived from established non-genetic risk factors as well as to clearly present this information to patient and health care providers.

X Demographics

X Demographics

The data shown below were collected from the profiles of 17 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 96 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Russia 1 1%
Canada 1 1%
Unknown 92 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 22%
Researcher 16 17%
Student > Master 13 14%
Professor > Associate Professor 6 6%
Student > Bachelor 6 6%
Other 18 19%
Unknown 16 17%
Readers by discipline Count As %
Medicine and Dentistry 29 30%
Agricultural and Biological Sciences 13 14%
Biochemistry, Genetics and Molecular Biology 12 13%
Computer Science 7 7%
Engineering 3 3%
Other 11 11%
Unknown 21 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 26 November 2020.
All research outputs
#2,759,220
of 24,155,398 outputs
Outputs from Frontiers in Genetics
#678
of 12,970 outputs
Outputs of similar age
#27,537
of 233,921 outputs
Outputs of similar age from Frontiers in Genetics
#9
of 129 outputs
Altmetric has tracked 24,155,398 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,970 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done particularly well, scoring higher than 94% 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 233,921 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 129 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 93% of its contemporaries.