Author:
Taggar Tushar,Sharma Subhag,Sharma Sanjay
Publisher
Springer Nature Switzerland
Reference22 articles.
1. Zhou, Q., Zou, H., Wang, Z.: Long-tailed multi-label retinal diseases recognition via relational learning and knowledge distillation. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds.) MICCAI 2022. LNCS, vol. 13432, pp. 709–718. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-16434-7_68
2. Cen, L.-P., et al.: Automatic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks. Nat. Commun. 12(1) (2021). https://doi.org/10.1038/s41467-021-25138-w
3. Lam, C., Yi, D., Guo, M., Lindsey, T.: Automated detection of diabetic retinopathy using deep learning. AMIA Jt. Summits Transl. Sci. Proc. 2018, 147–155 (2017). PMID: 29888061; PMCID: PMC5961805
4. He, J., Li, C., Ye, J., Qiao, Y., Gu, L.: Biomed. Sig. Process. Control 63, 102167 (2021). https://doi.org/10.1016/j.bspc.2020.102167
5. Pachade, S., et al.: Retinal fundus multi-disease image dataset (RFMiD): a dataset for multi-disease detection research. Data 6(2), 14 (2021). https://doi.org/10.3390/data6020014