Expert-Level Diagnosis of Nonpigmented Skin Cancer by Combined Convolutional Neural Networks | Zendy

Philipp Tschandl | Zendy; Cliff Rosendahl | Zendy; Bengü Nisa Akay | Zendy; Giuseppe Argenziano | Zendy; Andreas Blum | Zendy; Ralph P. Braun | Zendy; Horacio Cabo | Zendy; Jean-Yves Gourhant | Zendy; Jürgen Kreusch | Zendy; Aimilios Lallas | Zendy; Jan Lapins | Zendy; Ashfaq A. Marghoob | Zendy; Scott W. Menzies | Zendy; Nina Maria Neuber | Zendy; John Paoli | Zendy; Harold Rabinovitz | Zendy; Claus Rinner | Zendy; Alon Scope | Zendy; H. Peter Soyer | Zendy; Christoph Sinz | Zendy; L. Thomas | Zendy; Iris Zalaudek | Zendy; Harald Kittler | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Expert-Level Diagnosis of Nonpigmented Skin Cancer by Combined Convolutional Neural Networks

Author(s) -

Philipp Tschandl,

Cliff Rosendahl,

Bengü Nisa Akay,

Giuseppe Argenziano,

Andreas Blum,

Ralph P. Braun,

Horacio Cabo,

Jean-Yves Gourhant,

Jürgen Kreusch,

Aimilios Lallas,

Jan Lapins,

Ashfaq A. Marghoob,

Scott W. Menzies,

Nina Maria Neuber,

John Paoli,

Harold Rabinovitz,

Claus Rinner,

Alon Scope,

H. Peter Soyer,

Christoph Sinz,

L. Thomas,

Iris Zalaudek,

Harald Kittler

Publication year - 2018

Publication title -

jama dermatology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.128

H-Index - 166

eISSN - 2168-6084

pISSN - 2168-6068

DOI - 10.1001/jamadermatol.2018.4378

Subject(s) - medicine , receiver operating characteristic , medical diagnosis , convolutional neural network , skin cancer , artificial intelligence , cancer , pathology , computer science

Convolutional neural networks (CNNs) achieve expert-level accuracy in the diagnosis of pigmented melanocytic lesions. However, the most common types of skin cancer are nonpigmented and nonmelanocytic, and are more difficult to diagnose.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research