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Mendeley readers
Attention Score in Context
Title |
Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example
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Published in |
Frontiers in Genetics, August 2014
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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
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.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 24% |
United Kingdom | 3 | 18% |
Switzerland | 2 | 12% |
Philippines | 1 | 6% |
India | 1 | 6% |
Venezuela, Bolivarian Republic of | 1 | 6% |
Canada | 1 | 6% |
Italy | 1 | 6% |
Congo, The Democratic Republic of the | 1 | 6% |
Other | 0 | 0% |
Unknown | 2 | 12% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 8 | 47% |
Members of the public | 7 | 41% |
Practitioners (doctors, other healthcare professionals) | 2 | 12% |
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
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.