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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Predicting Alzheimer’s Disease Conversion From Mild Cognitive Impairment Using an Extreme Learning Machine-Based Grading Method With Multimodal Data
|
|---|---|
| Published in |
Frontiers in Aging Neuroscience, April 2020
|
| DOI | 10.3389/fnagi.2020.00077 |
| Pubmed ID | |
| Authors |
Weiming Lin, Qinquan Gao, Jiangnan Yuan, Zhiying Chen, Chenwei Feng, Weisheng Chen, Min Du, Tong Tong |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 14% |
| France | 1 | 14% |
| Switzerland | 1 | 14% |
| Unknown | 4 | 57% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 86% |
| Scientists | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 76 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 12 | 16% |
| Researcher | 9 | 12% |
| Student > Ph. D. Student | 9 | 12% |
| Unspecified | 3 | 4% |
| Student > Doctoral Student | 2 | 3% |
| Other | 6 | 8% |
| Unknown | 35 | 46% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 10 | 13% |
| Medicine and Dentistry | 5 | 7% |
| Engineering | 5 | 7% |
| Nursing and Health Professions | 3 | 4% |
| Neuroscience | 3 | 4% |
| Other | 13 | 17% |
| Unknown | 37 | 49% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 16 May 2020.
All research outputs
#2,497,265
of 23,201,298 outputs
Outputs from Frontiers in Aging Neuroscience
#852
of 4,903 outputs
Outputs of similar age
#61,182
of 370,774 outputs
Outputs of similar age from Frontiers in Aging Neuroscience
#21
of 103 outputs
Altmetric has tracked 23,201,298 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,903 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.2. This one has done well, scoring higher than 82% 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 370,774 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 83% of its contemporaries.
We're also able to compare this research output to 103 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.