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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep Multi-Magnification Similarity Learning for Histopathological Image Classification
|
|---|---|
| Published in |
IEEE Journal of Biomedical and Health Informatics, January 2023
|
| DOI | 10.1109/jbhi.2023.3237137 |
| Pubmed ID | |
| Authors |
Songhui Diao, Weiren Luo, Jiaxin Hou, Ricardo Lambo, Hamas A. AL-kuhali, Hanqing Zhao, Yinli Tian, Yaoqin Xie, Nazar Zaki, Wenjian Qin |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 24 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 10 | 42% |
| Student > Ph. D. Student | 2 | 8% |
| Researcher | 1 | 4% |
| Unknown | 11 | 46% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 10 | 42% |
| Computer Science | 2 | 8% |
| Unknown | 12 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 21. 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 06 April 2023.
All research outputs
#1,794,843
of 25,394,764 outputs
Outputs from IEEE Journal of Biomedical and Health Informatics
#30
of 1,831 outputs
Outputs of similar age
#37,823
of 471,969 outputs
Outputs of similar age from IEEE Journal of Biomedical and Health Informatics
#2
of 56 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,831 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 98% 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 471,969 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 56 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.