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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Identifying Early Mild Cognitive Impairment by Multi-Modality MRI-Based Deep Learning
|
|---|---|
| Published in |
Frontiers in Aging Neuroscience, September 2020
|
| DOI | 10.3389/fnagi.2020.00206 |
| Pubmed ID | |
| Authors |
Li Kang, Jingwan Jiang, Jianjun Huang, Tijiang Zhang |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 6 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 83% |
| Practitioners (doctors, other healthcare professionals) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 75 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 13% |
| Student > Master | 7 | 9% |
| Professor > Associate Professor | 5 | 7% |
| Lecturer | 5 | 7% |
| Student > Doctoral Student | 5 | 7% |
| Other | 21 | 28% |
| Unknown | 22 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 19 | 25% |
| Neuroscience | 7 | 9% |
| Engineering | 6 | 8% |
| Medicine and Dentistry | 5 | 7% |
| Psychology | 3 | 4% |
| Other | 7 | 9% |
| Unknown | 28 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 22 November 2020.
All research outputs
#2,613,655
of 23,243,271 outputs
Outputs from Frontiers in Aging Neuroscience
#902
of 4,918 outputs
Outputs of similar age
#69,044
of 399,399 outputs
Outputs of similar age from Frontiers in Aging Neuroscience
#25
of 113 outputs
Altmetric has tracked 23,243,271 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,918 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 81% 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 399,399 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 82% of its contemporaries.
We're also able to compare this research output to 113 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.