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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MediSyn: uncertainty-aware visualization of multiple biomedical datasets to support drug treatment selection
|
|---|---|
| Published in |
BMC Bioinformatics, September 2017
|
| DOI | 10.1186/s12859-017-1785-7 |
| Pubmed ID | |
| Authors |
Chen He, Luana Micallef, Zia-ur-Rehman Tanoli, Samuel Kaski, Tero Aittokallio, Giulio Jacucci |
X Demographics
The data shown below were collected from the profiles of 3 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 | 1 | 33% |
| Finland | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 34 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 9 | 26% |
| Student > Ph. D. Student | 4 | 12% |
| Professor | 3 | 9% |
| Researcher | 3 | 9% |
| Librarian | 2 | 6% |
| Other | 5 | 15% |
| Unknown | 8 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 9 | 26% |
| Medicine and Dentistry | 4 | 12% |
| Nursing and Health Professions | 2 | 6% |
| Chemistry | 2 | 6% |
| Neuroscience | 2 | 6% |
| Other | 7 | 21% |
| Unknown | 8 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 06 November 2017.
All research outputs
#17,932,284
of 26,017,215 outputs
Outputs from BMC Bioinformatics
#5,787
of 7,793 outputs
Outputs of similar age
#212,752
of 326,614 outputs
Outputs of similar age from BMC Bioinformatics
#71
of 101 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,793 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one is in the 17th percentile – i.e., 17% 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 326,614 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 101 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.