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%0 Journal Article
%1 Brinker2022-wg
%A Brinker, Titus J
%A Schmitt, Max
%A Krieghoff-Henning, Eva I
%A Barnhill, Raymond
%A Beltraminelli, Helmut
%A Braun, Stephan A
%A Carr, Richard
%A Fernandez-Figueras, Maria-Teresa
%A Ferrara, Gerardo
%A Fraitag, Sylvie
%A Gianotti, Raffaele
%A Llamas-Velasco, Mar
%A Müller, Cornelia S L
%A Perasole, Antonio
%A Requena, Luis
%A Sangueza, Omar P
%A Santonja, Carlos
%A Starz, Hans
%A Vale, Esmeralda
%A Weyers, Wolfgang
%A Hekler, Achim
%A Kather, Jakob N
%A Fröhling, Stefan
%A Krahl, Dieter
%A Holland-Letz, Tim
%A Utikal, Jochen S
%A Saggini, Andrea
%A Kutzner, Heinz
%D 2022
%I Elsevier BV
%J J. Am. Acad. Dermatol.
%K topic_lifescience
%N 3
%P 640--642
%T Diagnostic performance of artificial intelligence for histologic melanoma recognition compared to 18 international expert pathologists
%V 86
@article{Brinker2022-wg,
added-at = {2024-09-10T11:56:37.000+0200},
author = {Brinker, Titus J and Schmitt, Max and Krieghoff-Henning, Eva I and Barnhill, Raymond and Beltraminelli, Helmut and Braun, Stephan A and Carr, Richard and Fernandez-Figueras, Maria-Teresa and Ferrara, Gerardo and Fraitag, Sylvie and Gianotti, Raffaele and Llamas-Velasco, Mar and M{\"u}ller, Cornelia S L and Perasole, Antonio and Requena, Luis and Sangueza, Omar P and Santonja, Carlos and Starz, Hans and Vale, Esmeralda and Weyers, Wolfgang and Hekler, Achim and Kather, Jakob N and Fr{\"o}hling, Stefan and Krahl, Dieter and Holland-Letz, Tim and Utikal, Jochen S and Saggini, Andrea and Kutzner, Heinz},
biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/2f4cdd76a6bea92b64fcbf5baebb815a1/scadsfct},
copyright = {http://creativecommons.org/licenses/by/4.0/},
interhash = {08e3ac74e470553d22a60b380972f1ca},
intrahash = {f4cdd76a6bea92b64fcbf5baebb815a1},
journal = {J. Am. Acad. Dermatol.},
keywords = {topic_lifescience},
language = {en},
month = mar,
number = 3,
pages = {640--642},
publisher = {Elsevier BV},
timestamp = {2024-09-10T15:11:13.000+0200},
title = {Diagnostic performance of artificial intelligence for histologic melanoma recognition compared to 18 international expert pathologists},
volume = 86,
year = 2022
}