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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A Convolutional Neural Network Deep Learning Model Trained on CD Ulcers Images Accurately Identifies NSAID Ulcers
|
|---|---|
| Published in |
Frontiers in Medicine, August 2021
|
| DOI | 10.3389/fmed.2021.656493 |
| Pubmed ID | |
| Authors |
Eyal Klang, Uri Kopylov, Brynjulf Mortensen, Anders Damholt, Shelly Soffer, Yiftach Barash, Eli Konen, Ana Grinman, Reuma Margalit Yehuda, Martin Buckley, Fergus Shanahan, Rami Eliakim, Shomron Ben-Horin |
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 % |
|---|---|---|
| Spain | 3 | 50% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 67% |
| Scientists | 2 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 15 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 1 | 7% |
| Researcher | 1 | 7% |
| Other | 1 | 7% |
| Student > Doctoral Student | 1 | 7% |
| Unknown | 11 | 73% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 1 | 7% |
| Immunology and Microbiology | 1 | 7% |
| Medicine and Dentistry | 1 | 7% |
| Engineering | 1 | 7% |
| Unknown | 11 | 73% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 09 October 2021.
All research outputs
#7,338,030
of 23,310,485 outputs
Outputs from Frontiers in Medicine
#1,732
of 5,971 outputs
Outputs of similar age
#146,801
of 429,982 outputs
Outputs of similar age from Frontiers in Medicine
#132
of 424 outputs
Altmetric has tracked 23,310,485 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 5,971 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.5. This one has gotten more attention than average, scoring higher than 70% 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 429,982 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 65% of its contemporaries.
We're also able to compare this research output to 424 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 68% of its contemporaries.