Last Posted: May 19, 2020
- Predicting conversion to wet age-related macular degeneration using deep learning
J Yim et al, Nature Medicine, May 18, 2020 - Anti-VEGF Treatment and Response in Age-related Macular Degeneration: Disease's Susceptibility, Pharmacogenetics and Pharmacokinetics.
Maroñas Olalla et al. Current medicinal chemistry 2020 27(4) 549-569 - Outcome measures in juvenile X-linked retinoschisis: A systematic review.
Grigg John R et al. Eye (London, England) 2020 Apr - Deep-learning-based Prediction of Late Age-Related Macular Degeneration Progression.
Yan Qi et al. Nature machine intelligence 2020 Feb 2(2) 141-150 - Practice Guidelines for Ocular Telehealth-Diabetic Retinopathy, Third Edition.
Horton Mark B et al. Telemedicine journal and e-health : the official journal of the American Telemedicine Association 2020 Mar - Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma.
Zapata Miguel Angel et al. Clinical ophthalmology (Auckland, N.Z.) 2020 14419-429 - Genetic biomarkers in the VEGF pathway predicting response to anti-VEGF therapy in age-related macular degeneration.
Balikova Irina et al. BMJ open ophthalmology 2019 4(1) e000273 - The role of hypoxia-inducible factors in neovascular age-related macular degeneration: a gene therapy perspective.
Mammadzada Parviz et al. Cellular and molecular life sciences : CMLS 2019 Dec - Predictive genetics for AMD: Hype and hopes for genetics-based strategies for treatment and prevention.
Gorin Michael B et al. Experimental eye research 2019 Dec 107894 - Gene editing prospects for treating inherited retinal diseases.
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