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X Demographics
Mendeley readers
Attention Score in Context
Title |
Primary Categorizing and Masking Cerebral Small Vessel Disease Based on “Deep Learning System”
|
---|---|
Published in |
Frontiers in Neuroinformatics, May 2020
|
DOI | 10.3389/fninf.2020.00017 |
Pubmed ID | |
Authors |
Yunyun Duan, Wei Shan, Liying Liu, Qun Wang, Zhenzhou Wu, Pan Liu, Jiahao Ji, Yaou Liu, Kunlun He, Yongjun Wang |
X Demographics
The data shown below were collected from the profiles of 5 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 | 20% |
France | 1 | 20% |
Switzerland | 1 | 20% |
Unknown | 2 | 40% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 80% |
Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 32 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 5 | 16% |
Student > Ph. D. Student | 5 | 16% |
Researcher | 3 | 9% |
Other | 2 | 6% |
Student > Doctoral Student | 1 | 3% |
Other | 4 | 13% |
Unknown | 12 | 38% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 7 | 22% |
Computer Science | 3 | 9% |
Engineering | 3 | 9% |
Neuroscience | 3 | 9% |
Physics and Astronomy | 1 | 3% |
Other | 3 | 9% |
Unknown | 12 | 38% |
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 24 October 2021.
All research outputs
#13,766,781
of 23,342,232 outputs
Outputs from Frontiers in Neuroinformatics
#446
of 766 outputs
Outputs of similar age
#199,667
of 393,992 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#12
of 13 outputs
Altmetric has tracked 23,342,232 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 766 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. 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 393,992 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.