You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Convolutional Neural Networks-Based MRI Image Analysis for the Alzheimer’s Disease Prediction From Mild Cognitive Impairment
|
|---|---|
| Published in |
Frontiers in Neuroscience, November 2018
|
| DOI | 10.3389/fnins.2018.00777 |
| Pubmed ID | |
| Authors |
Weiming Lin, Tong Tong, Qinquan Gao, Di Guo, Xiaofeng Du, Yonggui Yang, Gang Guo, Min Xiao, Min Du, Xiaobo Qu, The Alzheimer’s Disease Neuroimaging Initiative |
X Demographics
The data shown below were collected from the profiles of 6 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 | 17% |
| United States | 1 | 17% |
| Thailand | 1 | 17% |
| Switzerland | 1 | 17% |
| Unknown | 2 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 50% |
| Practitioners (doctors, other healthcare professionals) | 2 | 33% |
| Scientists | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 334 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 334 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 53 | 16% |
| Student > Master | 39 | 12% |
| Researcher | 32 | 10% |
| Student > Doctoral Student | 20 | 6% |
| Student > Bachelor | 19 | 6% |
| Other | 38 | 11% |
| Unknown | 133 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 69 | 21% |
| Engineering | 40 | 12% |
| Neuroscience | 27 | 8% |
| Medicine and Dentistry | 19 | 6% |
| Biochemistry, Genetics and Molecular Biology | 9 | 3% |
| Other | 27 | 8% |
| Unknown | 143 | 43% |
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 23 November 2018.
All research outputs
#3,027,812
of 25,385,509 outputs
Outputs from Frontiers in Neuroscience
#2,023
of 11,542 outputs
Outputs of similar age
#61,141
of 364,877 outputs
Outputs of similar age from Frontiers in Neuroscience
#47
of 297 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,542 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. 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 364,877 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 297 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.