Discrimination Between Invasive and In Situ Melanomas Using Clinical Close-Up Images and a De Novo Convolutional Neural Network

Discrimination Between Invasive and In Situ Melanomas Using Clinical Close-Up Images and a De Novo Convolutional Neural Network

Background: Melanomas are often easy to recognize clinically but determining whether a melanoma is in situ (MIS) or invasive is often more challenging even with the aid of dermoscopy. Recently, convolutional neural networks (CNNs) have made significant and rapid advances within dermatology image ana...

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Bibliographic Details
Main Authors: Sam Polesie, Martin Gillstedt, Gustav Ahlgren, Hannah Ceder, Johan Dahlén Gyllencreutz, Julia Fougelberg, Eva Johansson Backman, Jenna Pakka, Oscar Zaar, John Paoli
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-09-01
Series:Frontiers in Medicine
Subjects:
artificial intelligence
clinical decision-making
melanoma
neural networks
computer
supervised machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2021.723914/full

Internet

https://www.frontiersin.org/articles/10.3389/fmed.2021.723914/full

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