| Title |
Automated emergent large vessel occlusion detection by artificial intelligence improves stroke workflow in a hub and spoke stroke system of care
|
|---|---|
| Published in |
Journal of NeuroInterventional Surgery, August 2021
|
| DOI | 10.1136/neurintsurg-2021-017714 |
| Pubmed ID | |
| Authors |
Lucas Elijovich, David Dornbos, Christopher Nickele, Andrei Alexandrov, Violiza Inoa-Acosta, Adam S Arthur, Daniel Hoit |
X Demographics
The data shown below were collected from the profiles of 10 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 | 40% |
| Korea, Republic of | 1 | 10% |
| Unknown | 5 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 70% |
| Scientists | 1 | 10% |
| Science communicators (journalists, bloggers, editors) | 1 | 10% |
| Practitioners (doctors, other healthcare professionals) | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 28 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 2 | 7% |
| Professor > Associate Professor | 2 | 7% |
| Researcher | 2 | 7% |
| Student > Ph. D. Student | 2 | 7% |
| Other | 1 | 4% |
| Other | 4 | 14% |
| Unknown | 15 | 54% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 25% |
| Unspecified | 1 | 4% |
| Biochemistry, Genetics and Molecular Biology | 1 | 4% |
| Environmental Science | 1 | 4% |
| Computer Science | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 16 | 57% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 28 July 2022.
All research outputs
#4,638,014
of 22,979,862 outputs
Outputs from Journal of NeuroInterventional Surgery
#921
of 2,366 outputs
Outputs of similar age
#105,193
of 430,298 outputs
Outputs of similar age from Journal of NeuroInterventional Surgery
#38
of 74 outputs
Altmetric has tracked 22,979,862 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,366 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one has gotten more attention than average, scoring higher than 60% 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 430,298 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 75% of its contemporaries.
We're also able to compare this research output to 74 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.