ARCHIVES

1. Brinker, T.J., et al. “Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task.” European Journal of Cancer, 113:47–54, 2019.
2. Brinker, T.J., et al. “Diagnostic performance of artificial intelligence for histologic melanoma recognition compared to 18 international expert pathologists.” JAMA Dermatology, 155(11):1241–1248, 2019.
3. Codella, N.C.F., et al. “Skin lesion analysis toward melanoma detection: A challenge at the 2017 ISIC.” IEEE Journal of Biomedical and Health Informatics, 23(2):547–552, 2019.
4. Esteva, A., et al. “Dermatologist-level classification of skin cancer with deep neural networks.” Nature, 542(7639):115–118, 2017.
5. Finnane, A., et al. “Teledermatology and artificial intelligence: Future directions for clinical practice.” British Journal of Dermatology, 183(3):423–429, 2020.
6. Goyal, M., et al. “AI in dermatology: Past, present, and future.” Seminars in Cutaneous Medicine and Surgery, 38(1):E13–E20, 2019.
7. Haenssle, H.A., et al. “Man against machine: Diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in clinical practice.” Annals of Oncology, 30(6):941-947, 2019.
8. Khan, A., et al. “A deep learning approach to melanoma detection using dermoscopic images.” International Journal of Computer Vision, 127(7):1052-1063, 2019.
9. Liao, P., et al. “Melanoma detection via deep learning-based analysis of skin images.” International Journal of Dermatology, 59(1):47-53, 2020.
10. Zhang, J., et al. “Deep learning for skin disease detection: A survey and future perspectives.” Journal of Biomedical Science and Engineering, 13(1):45-53, 2020.