A Robust Deep Learning Detection Approach for Retinopathy of Prematurity
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-47718-8_27
Reference26 articles.
1. Fierson, W.M.: American Academy of Ophthalmology; American Association for Pediatric Ophthalmology and Strabismus; American Association of Certified Orthoptists. Screening examination of premature infants for retinopathy of prematurity. Pediatrics 131(1), 189–195 (2013)
2. Blencowe, H., Lawn, J., Vazquez, T., Fielder, A., Gilbert, C.: Preterm-associated visual impairment and estimates of retinopathy of prematurity at regional and global levels for 2010. Pediatr. Res. 74(Suppl 1), 35–49 (2013)
3. Gilbert, C., Rahi, J., Eckstein, M., O’sullivan, J., Foster, A.: Retinopathy of prematurity in middle-income countries. Lancet 350(9070), 12–14 (1997)
4. Early treatment for retinopathy of prematurity cooperative group. Revised indications for the treatment of retinopathy of prematurity: results of the early treatment for retinopathy of prematurity randomized trial. Arch. Ophthalmol. 121(12), 1684–1694 (2003)
5. Gulshan, V., Peng, L., Coram, M., Stumpe, M.C., Wu, D., Narayanaswamy, A., Venugopalan, S., Widner, K., Madams, T., Cuadros, J., Kim, R., Raman, R., Nelson, P.C., Mega, J.L., Webster, D.R.: Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA 316(22), 2402–2410 (2016)
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