Reducing the Impact of Confounding Factors on Skin Cancer Classification via Image Segmentation: Technical Model Study

BACKGROUND: Studies have shown that artificial intelligence achieves similar or better performance than dermatologists in specific dermoscopic image classification tasks. However, artificial intelligence is susceptible to the influence of confounding factors within images (eg, skin markings), which...

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Detalles Bibliográficos
Autores principales: Maron, Roman C, Hekler, Achim, Krieghoff-Henning, Eva, Schmitt, Max, Schlager, Justin G, Utikal, Jochen S, Brinker, Titus J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8074854/
https://www.ncbi.nlm.nih.gov/pubmed/33764307
http://dx.doi.org/10.2196/21695

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8074854/
https://www.ncbi.nlm.nih.gov/pubmed/33764307
http://dx.doi.org/10.2196/21695

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