The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep Learning-Based Classification of Inflammatory Arthritis by Identification of Joint Shape Patterns—How Neural Networks Can Tell Us Where to “Deep Dive” Clinically
|
|---|---|
| Published in |
Frontiers in Medicine, March 2022
|
| DOI | 10.3389/fmed.2022.850552 |
| Pubmed ID | |
| Authors |
Lukas Folle, David Simon, Koray Tascilar, Gerhard Krönke, Anna-Maria Liphardt, Andreas Maier, Georg Schett, Arnd Kleyer |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 14% |
| Germany | 1 | 14% |
| Unknown | 5 | 71% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 86% |
| Practitioners (doctors, other healthcare professionals) | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 28 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 14% |
| Student > Doctoral Student | 2 | 7% |
| Unspecified | 2 | 7% |
| Student > Master | 2 | 7% |
| Lecturer | 1 | 4% |
| Other | 4 | 14% |
| Unknown | 13 | 46% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 4 | 14% |
| Medicine and Dentistry | 3 | 11% |
| Unspecified | 2 | 7% |
| Biochemistry, Genetics and Molecular Biology | 1 | 4% |
| Earth and Planetary Sciences | 1 | 4% |
| Other | 3 | 11% |
| Unknown | 14 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 75. 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 14 November 2023.
All research outputs
#563,817
of 25,359,594 outputs
Outputs from Frontiers in Medicine
#171
of 7,134 outputs
Outputs of similar age
#14,733
of 436,105 outputs
Outputs of similar age from Frontiers in Medicine
#14
of 619 outputs
Altmetric has tracked 25,359,594 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,134 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.7. This one has done particularly well, scoring higher than 97% 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 436,105 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 96% of its contemporaries.
We're also able to compare this research output to 619 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 97% of its contemporaries.