The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Automated Identification of Diabetic Retinopathy Using Deep Learning
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Cites
Deep Residual Learning for Image Recognition
He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474
ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155
LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126
Greedy function approximation: A gradient boosting machine
Friedman, J. H. (2001) · The Annals of Statistics · doi:10.1214/aos/1013203451 · Cited by 30,731
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Ioffe, S., & Szegedy, C. (2015) · arXiv · doi:10.48550/arxiv.1502.03167 · Cited by 27,818
Large-Scale Video Classification with Convolutional Neural Networks
Karpathy, A., Toderici, G., Shetty, S., Leung, T., Sukthankar, R., & Fei-Fei, L. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.223 · Cited by 6,354
Global estimates of diabetes prevalence for 2013 and projections for 2035
Guariguata, L., Whiting, D. R., Hambleton, I., Beagley, J., Linnenkamp, U., & Shaw, J. E. (2014) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2013.11.002 · Cited by 4,642
Prevalence of Diabetic Retinopathy in the United States, 2005-2008
Zhang, X., Saaddine, J. B., Chou, C.-F., Cotch, M. F., Cheng, Y. J., Geiss, L. S., Gregg, E. W., Albright, A. L., Klein, B. E. K., & Klein, R. (2010) · JAMA · doi:10.1001/jama.2010.1111 · Cited by 1,196
Abràmoff, M. D., Lou, Y., Erginay, A., Clarida, W., Amelon, R., Folk, J. C., & Niemeijer, M. (2016) · Investigative Opthalmology & Visual Science · doi:10.1167/iovs.16-19964 · Cited by 1,101
Global estimates of undiagnosed diabetes in adults
Beagley, J., Guariguata, L., Weil, C., & Motala, A. A. (2014) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2013.11.001 · Cited by 586
Cited by
Ting, D. S. W., Cheung, C. Y.-L., Lim, G., Tan, G. S. W., Quang, N. D., Gan, A., Hamzah, H., Garcia-Franco, R., San Yeo, I. Y., Lee, S. Y., et al. (2017) · JAMA · doi:10.1001/jama.2017.18152 · Cited by 2,402
Artificial intelligence and deep learning in ophthalmology
Ting, D. S. W., Pasquale, L. R., Peng, L., Campbell, J. P., Lee, A. Y., Raman, R., Tan, G. S. W., Schmetterer, L., Keane, P. A., & Wong, T. Y. (2019) · British Journal of Ophthalmology · doi:10.1136/bjophthalmol-2018-313173 · Cited by 1,554
Artificial Intelligence and Deep Learning in Ophthalmology
Wang, Z., Keane, P. A., Chiang, M., Cheung, C. Y., Wong, T. Y., & Ting, D. S. W. (2022) · Artificial Intelligence in Medicine · doi:10.1007/978-3-030-64573-1_200 · Cited by 1,524
Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis
Aggarwal, R., Sounderajah, V., Martin, G., Ting, D. S. W., Karthikesalingam, A., King, D., Ashrafian, H., & Darzi, A. (2021) · npj Digital Medicine · doi:10.1038/s41746-021-00438-z · Cited by 946
Li, Z., He, Y., Keel, S., Meng, W., Chang, R. T., & He, M. (2018) · Ophthalmology · doi:10.1016/j.ophtha.2018.01.023 · Cited by 830
Metadata
- Authors
- Gargeya, R., & Leng, T.
- Venue
- Ophthalmology
- Publisher
- Elsevier BV
- Published
- 2017-07
- Volume
- 124
- Issue
- 7
- Pages
- 962-969
- ISSN
- 0161-6420 (ISSN-L)
- OpenAlex
- W2598442119
- Cited by
- 1,362
- References
- 11
- FWCI
- 69.48
- Type
- journal article
- Language
- en
- Open access
- closed
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- Gargeya, R., & Leng, T. (2017). Automated Identification of Diabetic Retinopathy Using Deep Learning. Ophthalmology. https://doi.org/10.1016/j.ophtha.2017.02.008
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
