Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists

AbstractBackground. Deep learning convolutional neural networks (CNN) may facilitate melanoma detection, but data comparing a CNN’s diagnostic performance to l

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Bibliographic Details
Main Authors:	Hänßle, Holger (Author) , Müller-Christmann, Christine (Author) , Schneiderbauer, Roland (Author) , Toberer, Ferdinand (Author) , Enk, Alexander (Author) , Uhlmann, Lorenz (Author)
Format:	Article (Journal)
Language:	English
Published:	28 May 2018
In:	Annals of oncology Year: 2018, Volume: 29, Issue: 8, Pages: 1836-1842
ISSN:	1569-8041
DOI:	10.1093/annonc/mdy166
Online Access:	Verlag, Volltext: https://doi.org/10.1093/annonc/mdy166 Verlag, Volltext: https://academic.oup.com/annonc/article/29/8/1836/5004443
Author Notes:	H.A. Haenssle, C. Fink, R. Schneiderbauer, F. Toberer, T. Buhl, A. Blum, A. Kalloo, A. Ben Hadj Hassen, L. Thomas, A. Enk, & L. Uhlmann ; Reader study level-I and level-II Groups

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Summary:	AbstractBackground. Deep learning convolutional neural networks (CNN) may facilitate melanoma detection, but data comparing a CNN’s diagnostic performance to l
Item Description:	Gesehen am 20.08.2019
Physical Description:	Online Resource
ISSN:	1569-8041
DOI:	10.1093/annonc/mdy166