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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Applications of Deep Learning to Neuro-Imaging Techniques
|
|---|---|
| Published in |
Frontiers in Neurology, August 2019
|
| DOI | 10.3389/fneur.2019.00869 |
| Pubmed ID | |
| Authors |
Guangming Zhu, Bin Jiang, Liz Tong, Yuan Xie, Greg Zaharchuk, Max Wintermark |
X Demographics
The data shown below were collected from the profiles of 57 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 | 9% |
| India | 5 | 9% |
| Brazil | 2 | 4% |
| Germany | 2 | 4% |
| Switzerland | 2 | 4% |
| United Kingdom | 2 | 4% |
| Spain | 2 | 4% |
| Portugal | 1 | 2% |
| France | 1 | 2% |
| Other | 8 | 14% |
| Unknown | 27 | 47% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 44 | 77% |
| Scientists | 7 | 12% |
| Practitioners (doctors, other healthcare professionals) | 5 | 9% |
| Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 312 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 312 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 44 | 14% |
| Student > Master | 41 | 13% |
| Researcher | 35 | 11% |
| Student > Bachelor | 31 | 10% |
| Student > Doctoral Student | 21 | 7% |
| Other | 52 | 17% |
| Unknown | 88 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 46 | 15% |
| Computer Science | 42 | 13% |
| Medicine and Dentistry | 40 | 13% |
| Neuroscience | 24 | 8% |
| Biochemistry, Genetics and Molecular Biology | 10 | 3% |
| Other | 47 | 15% |
| Unknown | 103 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 64. 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 19 April 2022.
All research outputs
#653,710
of 25,192,722 outputs
Outputs from Frontiers in Neurology
#226
of 14,300 outputs
Outputs of similar age
#13,792
of 348,682 outputs
Outputs of similar age from Frontiers in Neurology
#9
of 307 outputs
Altmetric has tracked 25,192,722 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,300 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.5. This one has done particularly well, scoring higher than 98% 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 348,682 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 96% of its contemporaries.
We're also able to compare this research output to 307 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 97% of its contemporaries.