Melanoma recognition by a deep learning convolutional neural network—Performance in different melanoma subtypes and localisations
European Journal of Cancer2020Vol. 127, pp. 21–29
Citations Over TimeTop 10% of 2020 papers
Julia K. Winkler, Katharina Sies, Christine Fink, Ferdinand Toberer, Alexander Enk, Teresa Deinlein, Rainer Hofmann‐Wellenhof, L. Thomas, Aimilios Lallas, Andreas Blum, Wilhelm Stolz, Mohamed Souhayel Abassi, Tobias A. Fuchs, Albert Rosenberger, Holger A. Haenssle
Related Papers
- → Receiver Operating Characteristic (ROC) Curves: The Basics and Beyond(2024)19 cited
- → The Melanoma Epidemic: More Apparent Than Real?(1997)97 cited
- → The walking man approach to interpreting the receiver operating characteristic curve and area under the receiver operating characteristic curve(2023)22 cited
- → Relationship of cell-mediated cytotoxicity against melanoma cells to prognosis in melanoma patients(1978)41 cited
- → Inhibition of leukocyte migration in agarose by KC1 extracts of a human melanoma cell line grown in serum‐free medium(1975)16 cited