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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Development and Validation of a Dispatcher Identification Algorithm for Stroke Emergencies
|
|---|---|
| Published in |
Stroke, January 2012
|
| DOI | 10.1161/strokeaha.111.634980 |
| Pubmed ID | |
| Authors |
Sebastian Krebes, Martin Ebinger, André M. Baumann, Philipp A. Kellner, Michal Rozanski, Florian Doepp, Jan Sobesky, Thomas Gensecke, Bernd A. Leidel, Uwe Malzahn, Ian Wellwood, Peter U. Heuschmann, Heinrich J. Audebert |
| Abstract |
Recent innovations such as CT installation in ambulances may lead to earlier start of stroke-specific treatments. However, such technically complex mobile facilities require effective methods of correctly identifying patients before deployment. We aimed to develop and validate a new dispatcher identification algorithm for stroke emergencies. |
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 % |
|---|---|---|
| United States | 1 | 50% |
| Spain | 1 | 50% |
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 87 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 1% |
| United States | 1 | 1% |
| Russia | 1 | 1% |
| Canada | 1 | 1% |
| Unknown | 83 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 18% |
| Student > Master | 15 | 17% |
| Student > Ph. D. Student | 8 | 9% |
| Student > Bachelor | 8 | 9% |
| Other | 6 | 7% |
| Other | 23 | 26% |
| Unknown | 11 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 44 | 51% |
| Nursing and Health Professions | 6 | 7% |
| Neuroscience | 4 | 5% |
| Business, Management and Accounting | 2 | 2% |
| Agricultural and Biological Sciences | 2 | 2% |
| Other | 8 | 9% |
| Unknown | 21 | 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 25 March 2012.
All research outputs
#20,356,726
of 25,837,817 outputs
Outputs from Stroke
#11,077
of 12,622 outputs
Outputs of similar age
#203,407
of 253,215 outputs
Outputs of similar age from Stroke
#65
of 135 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 12,622 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.6. This one is in the 10th percentile – i.e., 10% 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 253,215 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 135 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.