Haggenmüller, Sarah; Maron, Roman C.; Hekler, Achim; Utikal, Jochen S.; Barata, Catarina; Barnhill, Raymond L.; Beltraminelli, Helmut; Berking, Carola; Betz-Stablein, Brigid; Blum, Andreas; Braun, Stephan A.; Carr, Richard; Combalia, Marc; Fernandez Figueras, Maria-Teresa; Ferrara, Gerardo; Fraitag, Sylvie; French, Lars E.; Gellrich, Frank F.; Ghoreschi, Kamran; Goebeler, Matthias; Guitera, Pascale; Haenssle, Holger A.; Haferkamp, Sebastian; Heinzerling, Lucie; Heppt, Markus V.; Hilke, Franz J.; Hobelsberger, Sarah; Krahl, Dieter; Kutzner, Heinz; Lallas, Aimilios; Liopyris, Konstantinos; Llamas-Velasco, Mar; Malvehy, Josep; Meier, Friedegund; Müller, Cornelia S.L.; Navarini, Alexander A.; Navarrete-Dechent, Cristián; Perasole, Antonio; Poch, Gabriela; Podlipnik, Sebastian; Requena, Luis; Rotemberg, Veronica M.; Saggini, Andrea; Sangueza, Omar P.; Santonja, Carlos; Schadendorf, Dirk; Schilling, Bastian; Schlaak, Max; Schlager, Justin G.; Sergon, Mildred; Sondermann, Wiebke; Soyer, H. Peter; Starz, Hans; Stolz, Wilhelm; Vale, Esmeralda; Weyers, Wolfgang; Zink, Alexander; Krieghoff-Henning, Eva I.; Kather, Jakob N.; Von Kalle, Christof; Lipka, Daniel B.; Fröhling, Stefan; Hauschild, Axel; Kittler, Harald; Brinker, Titus J. (European Journal of Cancer, 2021-10)
Background: Multiple studies have compared the performance of artificial intelligence (AI)–based models for automated skin cancer classification to human experts, thus setting the cornerstone for a ...
