Effects of Label Noise on Deep Learning-Based Skin Cancer Classification

Effects of Label Noise on Deep Learning-Based Skin Cancer Classification

Recent studies have shown that deep learning is capable of classifying dermatoscopic images at least as well as dermatologists. However, many studies in skin cancer classification utilize non-biopsy-verified training images. This imperfect ground truth introduces a systematic error, but the effects...

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Bibliographic Details
Main Authors: Achim Hekler, Jakob N. Kather, Eva Krieghoff-Henning, Jochen S. Utikal, Friedegund Meier, Frank F. Gellrich, Julius Upmeier zu Belzen, Lars French, Justin G. Schlager, Kamran Ghoreschi, Tabea Wilhelm, Heinz Kutzner, Carola Berking, Markus V. Heppt, Sebastian Haferkamp, Wiebke Sondermann, Dirk Schadendorf, Bastian Schilling, Benjamin Izar, Roman Maron, Max Schmitt, Stefan Fröhling, Daniel B. Lipka, Titus J. Brinker
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-05-01
Series:Frontiers in Medicine
Subjects:
dermatology
artificial intelligence
label noise
skin cancer
melanoma
nevi
Online Access:https://www.frontiersin.org/article/10.3389/fmed.2020.00177/full

Internet

https://www.frontiersin.org/article/10.3389/fmed.2020.00177/full

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