Deep Neural Network or Dermatologist?

Author:

Young Kyle,Booth Gareth,Simpson Becks,Dutton Reuben,Shrapnel Sally

Publisher

Springer International Publishing

Reference23 articles.

1. Aas, K., Jullum, M., Løland, A.: Explaining individual predictions when features are dependent: more accurate approximations to shapley values. arXiv preprint arXiv:1903.10464 (2019)

2. Adebayo, J., Gilmer, J., Muelly, M., Goodfellow, I., Hardt, M., Kim, B.: Sanity checks for saliency maps. In: Advances in Neural Information Processing Systems, pp. 9505–9515 (2018)

3. Brinker, T.J., et al.: Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task. Eur. J. Cancer 113, 47–54 (2019)

4. Brinker, T.J., et al.: Skin cancer classification using convolutional neural networks: systematic review. J. Med. Internet Res. 20(10), e11936 (2018)

5. Chen, J., Song, L., Wainwright, M.J., Jordan, M.I.: L-shapley and C-shapley: efficient model interpretation for structured data. arXiv preprint arXiv:1808.02610 (2018)

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