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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Translational AI and Deep Learning in Diagnostic Pathology
|
|---|---|
| Published in |
Frontiers in Medicine, October 2019
|
| DOI | 10.3389/fmed.2019.00185 |
| Pubmed ID | |
| Authors |
Ahmed Serag, Adrian Ion-Margineanu, Hammad Qureshi, Ryan McMillan, Marie-Judith Saint Martin, Jim Diamond, Paul O'Reilly, Peter Hamilton |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 25% |
| Venezuela, Bolivarian Republic of | 1 | 13% |
| United Kingdom | 1 | 13% |
| Switzerland | 1 | 13% |
| Unknown | 3 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 63% |
| Practitioners (doctors, other healthcare professionals) | 2 | 25% |
| Science communicators (journalists, bloggers, editors) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 331 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 331 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 50 | 15% |
| Student > Ph. D. Student | 46 | 14% |
| Student > Master | 38 | 11% |
| Student > Bachelor | 27 | 8% |
| Other | 20 | 6% |
| Other | 52 | 16% |
| Unknown | 98 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 51 | 15% |
| Medicine and Dentistry | 49 | 15% |
| Engineering | 30 | 9% |
| Biochemistry, Genetics and Molecular Biology | 22 | 7% |
| Agricultural and Biological Sciences | 18 | 5% |
| Other | 51 | 15% |
| Unknown | 110 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 08 September 2022.
All research outputs
#5,310,838
of 26,017,215 outputs
Outputs from Frontiers in Medicine
#1,515
of 7,297 outputs
Outputs of similar age
#97,936
of 365,659 outputs
Outputs of similar age from Frontiers in Medicine
#23
of 79 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,297 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.6. This one has done well, scoring higher than 79% 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 365,659 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 79 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.