Linking disease activity with optical coherence tomography angiography in neovascular age related macular degeneration using artificial intelligence
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Publisher
Springer Science and Business Media LLC
Link
https://www.nature.com/articles/s41598-024-70234-8.pdf
Reference34 articles.
1. Wong, W. L. et al. Global prevalence of age-related macular degeneration and disease burden projection for 2020 and 2040: A systematic review and meta-analysis. Lancet Glob. Health 2(2), e106–e116. https://doi.org/10.1016/S2214-109X(13)70145-1 (2014).
2. Schmidt-Erfurth, U. et al. Guidelines for the management of neovascular age-related macular degeneration by the European Society of Retina Specialists (EURETINA). Br. J. Ophthalmol. 98(9), 1144–1167. https://doi.org/10.1136/bjophthalmol-2014-305702 (2014).
3. Schlegl, T. et al. Fully automated detection and quantification of macular fluid in OCT using deep learning. Ophthalmology 125(4), 549–558. https://doi.org/10.1016/J.OPHTHA.2017.10.031 (2018).
4. Bogunovic, H. et al. Prediction of anti-VEGF treatment requirements in neovascular AMD using a machine learning approach. Investig. Opthalmol. Vis. Sci. 58(7), 3240. https://doi.org/10.1167/iovs.16-21053 (2017).
5. Schmidt-Erfurth, U., Vogl, W. D., Jampol, L. M., Bogunovi, H. & Bogunović, H. Application of automated quantification of fluid volumes to anti-VEGF therapy of neovascular age-related macular degeneration. Ophthalmology 127, 1211–1219. https://doi.org/10.1016/j.ophtha.2020.03.010 (2020).
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