Diagnostic performance of a deep learning convolutional neural network in the differentiation of combined naevi and melanomas-Reference-Cited by-同舟云学术

Diagnostic performance of a deep learning convolutional neural network in the differentiation of combined naevi and melanomas

Published:2020-01-21 Issue:6 Volume:34 Page:1355-1361
ISSN:0926-9959
Container-title:Journal of the European Academy of Dermatology and Venereology
language:en
Short-container-title:J Eur Acad Dermatol Venereol

Author:

Fink C.¹^ORCID,Blum A.²,Buhl T.³,Mitteldorf C.³,Hofmann‐Wellenhof R.⁴,Deinlein T.⁴^ORCID,Stolz W.⁵,Trennheuser L.¹,Cussigh C.¹,Deltgen D.¹,Winkler J.K.¹,Toberer F.¹^ORCID,Enk A.¹,Rosenberger A.⁶,Haenssle H.A.¹^ORCID

Affiliation:

1. Department of Dermatology University of Heidelberg Heidelberg Germany

2. Public, Private and Teaching Practice Konstanz Germany

3. Department of Dermatology and Allergology University Medical Center Göttingen Göttingen Germany

4. Department of Dermatology and Venerology Medical University of Graz Graz Austria

5. Department of Dermatology, Allergology and Environmental Medicine II Hospital Thalkirchner Street Munich Germany

6. Department of Genetic Epidemiology University Medical Center of Goettingen Goettingen Germany

Publisher

Wiley

Subject

Infectious Diseases,Dermatology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jdv.16165

Reference15 articles.

1. Trends in incidence and predictions of cutaneous melanoma across Europe up to 2015

2. Melanoma screening: A plan for improving early detection

3. Dermoscopy compared with naked eye examination for the diagnosis of primary melanoma: a meta-analysis of studies performed in a clinical setting

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

5. Dermatologist-level classification of skin cancer with deep neural networks

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