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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Objective and Automated Detection of Diffuse White Matter Abnormality in Preterm Infants Using Deep Convolutional Neural Networks
|
|---|---|
| Published in |
Frontiers in Neuroscience, June 2019
|
| DOI | 10.3389/fnins.2019.00610 |
| Pubmed ID | |
| Authors |
Hailong Li, Nehal A. Parikh, Jinghua Wang, Stephanie Merhar, Ming Chen, Milan Parikh, Scott Holland, Lili He |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 25% |
| Switzerland | 1 | 25% |
| United States | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Practitioners (doctors, other healthcare professionals) | 1 | 25% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 35 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 17% |
| Student > Ph. D. Student | 6 | 17% |
| Student > Bachelor | 3 | 9% |
| Student > Master | 3 | 9% |
| Student > Postgraduate | 2 | 6% |
| Other | 1 | 3% |
| Unknown | 14 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 11% |
| Computer Science | 2 | 6% |
| Neuroscience | 2 | 6% |
| Agricultural and Biological Sciences | 1 | 3% |
| Psychology | 1 | 3% |
| Other | 4 | 11% |
| Unknown | 21 | 60% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 July 2019.
All research outputs
#15,906,098
of 25,622,179 outputs
Outputs from Frontiers in Neuroscience
#6,760
of 11,639 outputs
Outputs of similar age
#202,878
of 368,257 outputs
Outputs of similar age from Frontiers in Neuroscience
#190
of 317 outputs
Altmetric has tracked 25,622,179 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,639 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 39th percentile – i.e., 39% 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 368,257 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 317 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.