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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Different Machine Learning and Deep Learning Methods for the Classification of Colorectal Cancer Lymph Node Metastasis Images
|
|---|---|
| Published in |
Frontiers in Bioengineering and Biotechnology, January 2021
|
| DOI | 10.3389/fbioe.2020.620257 |
| Pubmed ID | |
| Authors |
Jin Li, Peng Wang, Yang Zhou, Hong Liang, Kuan Luan |
X Demographics
The data shown below were collected from the profiles of 35 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 2 | 6% |
| United Arab Emirates | 2 | 6% |
| India | 1 | 3% |
| United Kingdom | 1 | 3% |
| Netherlands | 1 | 3% |
| Poland | 1 | 3% |
| France | 1 | 3% |
| Germany | 1 | 3% |
| Canada | 1 | 3% |
| Other | 4 | 11% |
| Unknown | 20 | 57% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 25 | 71% |
| Practitioners (doctors, other healthcare professionals) | 5 | 14% |
| Scientists | 4 | 11% |
| Science communicators (journalists, bloggers, editors) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 26 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 15% |
| Unspecified | 3 | 12% |
| Student > Bachelor | 3 | 12% |
| Professor > Associate Professor | 2 | 8% |
| Researcher | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 12 | 46% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 3 | 12% |
| Biochemistry, Genetics and Molecular Biology | 2 | 8% |
| Engineering | 2 | 8% |
| Computer Science | 2 | 8% |
| Agricultural and Biological Sciences | 1 | 4% |
| Other | 6 | 23% |
| Unknown | 10 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 2021.
All research outputs
#2,235,241
of 25,305,422 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#269
of 8,395 outputs
Outputs of similar age
#60,033
of 522,197 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#16
of 353 outputs
Altmetric has tracked 25,305,422 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,395 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done particularly well, scoring higher than 96% 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 522,197 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 88% of its contemporaries.
We're also able to compare this research output to 353 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 95% of its contemporaries.