Integrating Patient Data Into Skin Cancer Classification Using Convolutional Neural Networks: Systematic Review

• Main Authors: Julia Höhn (Author), Achim Hekler (Author), Eva Krieghoff-Henning (Author), Jakob Nikolas Kather (Author), Jochen Sven Utikal (Author), Friedegund Meier (Author), Frank Friedrich Gellrich (Author), Axel Hauschild (Author), Lars French (Author), Justin Gabriel Schlager (Author), Kamran Ghoreschi (Author), Tabea Wilhelm (Author), Heinz Kutzner (Author), Markus Heppt (Author), Sebastian Haferkamp (Author), Wiebke Sondermann (Author), Dirk Schadendorf (Author), Bastian Schilling (Author), Roman C Maron (Author), Max Schmitt (Author), Tanja Jutzi (Author), Stefan Fröhling (Author), Daniel B Lipka (Author), Titus Josef Brinker (Author)
• Format: Book
• Published: JMIR Publications, 2021-07-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

BackgroundRecent years have been witnessing a substantial improvement in the accuracy of skin cancer classification using convolutional neural networks (CNNs). CNNs perform on par with or better than dermatologists with respect to the classification tasks of single images. However, in clinical pract...