Difficulty-Aware Meta-learning for Rare Disease Diagnosis-Reference-Cited by-同舟云学术

Difficulty-Aware Meta-learning for Rare Disease Diagnosis

Published:2020 Issue: Volume: Page:357-366
ISSN:0302-9743
Container-title:Medical Image Computing and Computer Assisted Intervention – MICCAI 2020
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Author:

Li Xiaomeng,Yu Lequan,Jin Yueming,Fu Chi-Wing,Xing Lei,Heng Pheng-Ann

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-59710-8_35

Reference15 articles.

1. Codella, N.C., et al.: Skin lesion analysis toward melanoma detection challenge. In: IEEE International Symposium on Biomedical Imaging, pp. 168–172. IEEE (2018)

2. Finn, C., Abbeel, P., Levine, S.: Model-agnostic meta-learning for fast adaptation of deep networks. In: ICML, pp. 1126–1135. JMLR.org (2017)

3. Huang, G., Liu, Z., Van Der Maaten, L., Weinberger, K.Q.: Densely connected convolutional networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4700–4708 (2017)

4. Jia, J., Wang, R., An, Z., Guo, Y., Ni, X., Shi, T.: Rdad: a machine learning system to support phenotype-based rare disease diagnosis. Front. Genet. 9, 587 (2018)

5. Khoury, M., Valdez, R.: Rare diseases, genomics and public health: an expanding intersection. Genomics and Health Impact Blog (2016)

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