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Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task

Overview of attention for article published in European Journal of Cancer (1965), April 2019
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#27 of 8,865)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
16 news outlets
blogs
1 blog
twitter
255 X users
patent
2 patents
facebook
2 Facebook pages
reddit
10 Redditors

Readers on

mendeley
523 Mendeley
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Article details
Title
Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task
Published in
European Journal of Cancer (1965), April 2019
DOI 10.1016/j.ejca.2019.04.001
Pubmed ID
Authors

Titus J. Brinker, Achim Hekler, Alexander H. Enk, Joachim Klode, Axel Hauschild, Carola Berking, Bastian Schilling, Sebastian Haferkamp, Dirk Schadendorf, Tim Holland-Letz, Jochen S. Utikal, Christof von Kalle, Collaborators, Wiebke Ludwig-Peitsch, Judith Sirokay, Lucie Heinzerling, Magarete Albrecht, Katharina Baratella, Lena Bischof, Eleftheria Chorti, Anna Dith, Christina Drusio, Nina Giese, Emmanouil Gratsias, Klaus Griewank, Sandra Hallasch, Zdenka Hanhart, Saskia Herz, Katja Hohaus, Philipp Jansen, Finja Jockenhöfer, Theodora Kanaki, Sarah Knispel, Katja Leonhard, Anna Martaki, Liliana Matei, Johanna Matull, Alexandra Olischewski, Maximilian Petri, Jan-Malte Placke, Simon Raub, Katrin Salva, Swantje Schlott, Elsa Sody, Nadine Steingrube, Ingo Stoffels, Selma Ugurel, Anne Zaremba, Christoffer Gebhardt, Nina Booken, Maria Christolouka, Kristina Buder-Bakhaya, Therezia Bokor-Billmann, Alexander Enk, Patrick Gholam, Holger Hänßle, Martin Salzmann, Sarah Schäfer, Knut Schäkel, Timo Schank, Ann-Sophie Bohne, Sophia Deffaa, Katharina Drerup, Friederike Egberts, Anna-Sophie Erkens, Benjamin Ewald, Sandra Falkvoll, Sascha Gerdes, Viola Harde, Axel Hauschild, Marion Jost, Katja Kosova, Laetitia Messinger, Malte Metzner, Kirsten Morrison, Rogina Motamedi, Anja Pinczker, Anne Rosenthal, Natalie Scheller, Thomas Schwarz, Dora Stölzl, Federieke Thielking, Elena Tomaschewski, Ulrike Wehkamp, Michael Weichenthal, Oliver Wiedow, Claudia Maria Bär, Sophia Bender-Säbelkampf, Marc Horbrügger, Ante Karoglan, Luise Kraas, Jörg Faulhaber, Cyrill Geraud, Ze Guo, Philipp Koch, Miriam Linke, Nolwenn Maurier, Verena Müller, Benjamin Thomas, Jochen Sven Utikal, Ali Saeed M. Alamri, Andrea Baczako, Carola Berking, Matthias Betke, Carolin Haas, Daniela Hartmann, Markus V. Heppt, Katharina Kilian, Sebastian Krammer, Natalie Lidia Lapczynski, Sebastian Mastnik, Suzan Nasifoglu, Cristel Ruini, Elke Sattler, Max Schlaak, Hans Wolff, Birgit Achatz, Astrid Bergbreiter, Konstantin Drexler, Monika Ettinger, Sebastian Haferkamp, Anna Halupczok, Marie Hegemann, Verena Dinauer, Maria Maagk, Marion Mickler, Biance Philipp, Anna Wilm, Constanze Wittmann, Anja Gesierich, Valerie Glutsch, Katrin Kahlert, Andreas Kerstan, Bastian Schilling, Philipp Schrüfer

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X Demographics

X Demographics

The data shown below were collected from the profiles of 255 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 523 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 523 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Bachelor 44 8%
Student > Master 42 8%
Student > Ph. D. Student 37 7%
Researcher 32 6%
Student > Doctoral Student 20 4%
Other 80 15%
Unknown 268 51%
Readers by discipline
Readers by discipline Count As %
Computer Science 86 16%
Medicine and Dentistry 64 12%
Engineering 35 7%
Biochemistry, Genetics and Molecular Biology 12 2%
Business, Management and Accounting 8 2%
Other 38 7%
Unknown 280 54%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 298. 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 12 March 2026.
All research outputs
#147,666
of 34,586,309 outputs
Outputs from European Journal of Cancer (1965)
#27
of 8,865 outputs
Outputs of similar age
#2,519
of 395,974 outputs
Outputs of similar age from European Journal of Cancer (1965)
#1
of 69 outputs
Altmetric has tracked 34,586,309 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,865 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.2. This one has done particularly well, scoring higher than 99% 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 395,974 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 99% of its contemporaries.
We're also able to compare this research output to 69 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 98% of its contemporaries.