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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Machine Learning Models for Multiparametric Glioma Grading With Quantitative Result Interpretations
|
|---|---|
| Published in |
Frontiers in Neuroscience, January 2019
|
| DOI | 10.3389/fnins.2018.01046 |
| Pubmed ID | |
| Authors |
Xiuying Wang, Dingqian Wang, Zhigang Yao, Bowen Xin, Bao Wang, Chuanjin Lan, Yejun Qin, Shangchen Xu, Dazhong He, Yingchao Liu |
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 % |
|---|---|---|
| Saudi Arabia | 1 | 20% |
| Switzerland | 1 | 20% |
| United States | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 70 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 11% |
| Researcher | 7 | 10% |
| Student > Master | 7 | 10% |
| Student > Doctoral Student | 6 | 9% |
| Student > Bachelor | 6 | 9% |
| Other | 12 | 17% |
| Unknown | 24 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 13 | 19% |
| Medicine and Dentistry | 10 | 14% |
| Engineering | 8 | 11% |
| Biochemistry, Genetics and Molecular Biology | 3 | 4% |
| Linguistics | 1 | 1% |
| Other | 7 | 10% |
| Unknown | 28 | 40% |
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 04 February 2019.
All research outputs
#16,087,553
of 26,215,093 outputs
Outputs from Frontiers in Neuroscience
#6,745
of 11,786 outputs
Outputs of similar age
#246,616
of 449,894 outputs
Outputs of similar age from Frontiers in Neuroscience
#162
of 308 outputs
Altmetric has tracked 26,215,093 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,786 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 42nd percentile – i.e., 42% 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 449,894 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 308 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.