Man against machine reloaded: performance of a market-approved convolutional neural network in classifying a broad spectrum of skin lesions in comparison with 96 dermatologists working under less artificial conditions.
Τίτλος | Man against machine reloaded: performance of a market-approved convolutional neural network in classifying a broad spectrum of skin lesions in comparison with 96 dermatologists working under less artificial conditions. |
Publication Type | Journal Article |
Year of Publication | 2020 |
Authors | Haenssle, H. A., Fink C., Toberer F., Winkler J., Stolz W., Deinlein T., Hofmann-Wellenhof R., Lallas A., Emmert S., Buhl T., Zutt M., Blum A., Abassi M. S., Thomas L., Tromme I., Tschandl P., Enk A., & Rosenberger A. |
Corporate Authors | Reader Study Level I and Level II Groups |
Journal | Ann Oncol |
Volume | 31 |
Issue | 1 |
Pagination | 137-143 |
Date Published | 2020 01 |
ISSN | 1569-8041 |
Abstract | BACKGROUND: Convolutional neural networks (CNNs) efficiently differentiate skin lesions by image analysis. Studies comparing a market-approved CNN in a broad range of diagnoses to dermatologists working under less artificial conditions are lacking. |
DOI | 10.1016/j.annonc.2019.10.013 |
Alternate Journal | Ann Oncol |
PubMed ID | 31912788 |