You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Effects of Label Noise on Deep Learning-Based Skin Cancer Classification
|
|---|---|
| Published in |
Frontiers in Medicine, May 2020
|
| DOI | 10.3389/fmed.2020.00177 |
| Pubmed ID | |
| Authors |
Achim Hekler, Jakob N. Kather, Eva Krieghoff-Henning, Jochen S. Utikal, Friedegund Meier, Frank F. Gellrich, Julius Upmeier zu Belzen, Lars French, Justin G. Schlager, Kamran Ghoreschi, Tabea Wilhelm, Heinz Kutzner, Carola Berking, Markus V. Heppt, Sebastian Haferkamp, Wiebke Sondermann, Dirk Schadendorf, Bastian Schilling, Benjamin Izar, Roman Maron, Max Schmitt, Stefan Fröhling, Daniel B. Lipka, Titus J. Brinker |
X Demographics
The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 4 | 36% |
| United States | 1 | 9% |
| France | 1 | 9% |
| United Kingdom | 1 | 9% |
| Unknown | 4 | 36% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 55% |
| Scientists | 4 | 36% |
| Practitioners (doctors, other healthcare professionals) | 1 | 9% |
Mendeley readers
The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 61 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 13% |
| Student > Ph. D. Student | 8 | 13% |
| Researcher | 6 | 10% |
| Student > Doctoral Student | 3 | 5% |
| Student > Bachelor | 3 | 5% |
| Other | 7 | 11% |
| Unknown | 26 | 43% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 15 | 25% |
| Engineering | 8 | 13% |
| Medicine and Dentistry | 6 | 10% |
| Biochemistry, Genetics and Molecular Biology | 2 | 3% |
| Chemical Engineering | 1 | 2% |
| Other | 3 | 5% |
| Unknown | 26 | 43% |
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 14 June 2020.
All research outputs
#4,761,374
of 23,208,901 outputs
Outputs from Frontiers in Medicine
#1,193
of 5,921 outputs
Outputs of similar age
#110,261
of 382,491 outputs
Outputs of similar age from Frontiers in Medicine
#47
of 155 outputs
Altmetric has tracked 23,208,901 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 5,921 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 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 382,491 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 71% of its contemporaries.
We're also able to compare this research output to 155 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 69% of its contemporaries.