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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Applying Deep Learning to Accelerated Clinical Brain Magnetic Resonance Imaging for Multiple Sclerosis
|
|---|---|
| Published in |
Frontiers in Neurology, September 2021
|
| DOI | 10.3389/fneur.2021.685276 |
| Pubmed ID | |
| Authors |
Ashika Mani, Tales Santini, Radhika Puppala, Megan Dahl, Shruthi Venkatesh, Elizabeth Walker, Megan DeHaven, Cigdem Isitan, Tamer S. Ibrahim, Long Wang, Tao Zhang, Enhao Gong, Jessica Barrios-Martinez, Fang-Cheng Yeh, Robert Krafty, Joseph M. Mettenburg, Zongqi Xia |
X Demographics
The data shown below were collected from the profiles of 12 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 | 5 | 42% |
| Netherlands | 1 | 8% |
| India | 1 | 8% |
| Switzerland | 1 | 8% |
| Unknown | 4 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 58% |
| Practitioners (doctors, other healthcare professionals) | 3 | 25% |
| Scientists | 2 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 25 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 3 | 12% |
| Student > Doctoral Student | 2 | 8% |
| Student > Ph. D. Student | 2 | 8% |
| Researcher | 2 | 8% |
| Student > Postgraduate | 2 | 8% |
| Other | 2 | 8% |
| Unknown | 12 | 48% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 16% |
| Engineering | 3 | 12% |
| Agricultural and Biological Sciences | 1 | 4% |
| Neuroscience | 1 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 15 | 60% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 17 March 2022.
All research outputs
#2,336,847
of 23,885,338 outputs
Outputs from Frontiers in Neurology
#1,180
of 12,926 outputs
Outputs of similar age
#53,740
of 421,772 outputs
Outputs of similar age from Frontiers in Neurology
#38
of 681 outputs
Altmetric has tracked 23,885,338 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,926 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. 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 421,772 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 87% of its contemporaries.
We're also able to compare this research output to 681 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.