You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Can multiple SNP testing in BRCA2 and BRCA1 female carriers be used to improve risk prediction models in conjunction with clinical assessment?
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, October 2014
|
| DOI | 10.1186/1472-6947-14-87 |
| Pubmed ID | |
| Authors |
Mattia CF Prosperi, Sarah L Ingham, Anthony Howell, Fiona Lalloo, Iain E Buchan, Dafydd Gareth Evans |
| Abstract |
Several single nucleotide polymorphisms (SNPs) at different loci have been associated with breast cancer susceptibility, accounting for around 10% of the familial component. Recent studies have found direct associations between specific SNPs and breast cancer in BRCA1/2 mutation carriers. Our aim was to determine whether validated susceptibility SNP scores improve the predictive ability of risk models in comparison/conjunction to other clinical/demographic information. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 3% |
| Unknown | 36 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 5 | 14% |
| Researcher | 5 | 14% |
| Student > Master | 5 | 14% |
| Student > Ph. D. Student | 4 | 11% |
| Professor | 2 | 5% |
| Other | 10 | 27% |
| Unknown | 6 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 13 | 35% |
| Agricultural and Biological Sciences | 6 | 16% |
| Biochemistry, Genetics and Molecular Biology | 2 | 5% |
| Engineering | 2 | 5% |
| Computer Science | 2 | 5% |
| Other | 5 | 14% |
| Unknown | 7 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 03 October 2014.
All research outputs
#14,786,597
of 22,765,347 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,225
of 1,984 outputs
Outputs of similar age
#139,811
of 253,597 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#17
of 23 outputs
Altmetric has tracked 22,765,347 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,984 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 34th percentile – i.e., 34% of its peers scored the same or lower than it.
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 253,597 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.