Using multiple real-world dermoscopic photographs of one lesion improves melanoma classification via deep learning

Hekler A, Maron RC, Haggenmüller S, Schmitt M, Wies C, Utikal JS, Meier F, Hobelsberger S, Gellrich FF, Sergon M, Hauschild A, French LE, Heinzerling L, Schlager JG, Ghoreschi K, Schlaak M, Hilke FJ, Poch G, Korsing S, Berking C, Heppt M, Erdmann M, Haferkamp S, Drexler K, Schadendorf D, Sondermann W, Goebeler M, Schilling B, Kather JN, Krieghoff-Henning E, Brinker TJ (2024)


Publication Type: Journal article

Publication year: 2024

Journal

DOI: 10.1016/j.jaad.2023.11.065

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How to cite

APA:

Hekler, A., Maron, R.C., Haggenmüller, S., Schmitt, M., Wies, C., Utikal, J.S.,... Brinker, T.J. (2024). Using multiple real-world dermoscopic photographs of one lesion improves melanoma classification via deep learning. Journal of the American Academy of Dermatology. https://doi.org/10.1016/j.jaad.2023.11.065

MLA:

Hekler, Achim, et al. "Using multiple real-world dermoscopic photographs of one lesion improves melanoma classification via deep learning." Journal of the American Academy of Dermatology (2024).

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