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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Detalles Bibliográficos
Autores principales: Hekler, Achim, Kather, Jakob N., Krieghoff-Henning, Eva, Utikal, Jochen S., Meier, Friedegund, Gellrich, Frank F., Upmeier zu Belzen, Julius, French, Lars, Schlager, Justin G., Ghoreschi, Kamran, Wilhelm, Tabea, Kutzner, Heinz, Berking, Carola, Heppt, Markus V., Haferkamp, Sebastian, Sondermann, Wiebke, Schadendorf, Dirk, Schilling, Bastian, Izar, Benjamin, Maron, Roman, Schmitt, Max, Fröhling, Stefan, Lipka, Daniel B., Brinker, Titus J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7218064/
https://www.ncbi.nlm.nih.gov/pubmed/32435646
http://dx.doi.org/10.3389/fmed.2020.00177

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7218064/
https://www.ncbi.nlm.nih.gov/pubmed/32435646
http://dx.doi.org/10.3389/fmed.2020.00177

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