| Title |
A predictive algorithm to identify genes that discriminate individuals with fibromyalgia syndrome diagnosis from healthy controls
|
|---|---|
| Published in |
Journal of Pain Research, November 2018
|
| DOI | 10.2147/jpr.s169499 |
| Pubmed ID | |
| Authors |
Nada Lukkahatai, Brian Walitt, Enrique J Deandrés-Galiana, Juan Luis Fernández-Martínez, Leorey N Saligan |
X Demographics
The data shown below were collected from the profiles of 24 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 Kingdom | 6 | 25% |
| United States | 6 | 25% |
| Colombia | 2 | 8% |
| Australia | 2 | 8% |
| Germany | 1 | 4% |
| Spain | 1 | 4% |
| Unknown | 6 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 20 | 83% |
| Practitioners (doctors, other healthcare professionals) | 3 | 13% |
| Scientists | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 45 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 16% |
| Student > Master | 6 | 13% |
| Student > Doctoral Student | 2 | 4% |
| Other | 2 | 4% |
| Professor | 2 | 4% |
| Other | 5 | 11% |
| Unknown | 21 | 47% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 10 | 22% |
| Nursing and Health Professions | 6 | 13% |
| Computer Science | 2 | 4% |
| Psychology | 2 | 4% |
| Agricultural and Biological Sciences | 1 | 2% |
| Other | 3 | 7% |
| Unknown | 21 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 24. 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 07 June 2019.
All research outputs
#1,564,978
of 25,164,268 outputs
Outputs from Journal of Pain Research
#185
of 1,953 outputs
Outputs of similar age
#33,268
of 357,503 outputs
Outputs of similar age from Journal of Pain Research
#10
of 85 outputs
Altmetric has tracked 25,164,268 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,953 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 done particularly well, scoring higher than 90% 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 357,503 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 85 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.