Integrating Machine Learning and Traditional Survival Analysis to Identify Key Predictors of Foveal Involvement in Geographic Atrophy
Author:
Affiliation:
1. School of Medicine, Vita-Salute San Raffaele University, Milan, Italy
2. Department of Ophthalmology, IRCCS San Raffaele Scientific Institute, Milan, Italy
3. https://orcid.org/0000-0003-2938-0409
Publisher
Association for Research in Vision and Ophthalmology (ARVO)
Reference32 articles.
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2. Enlargement of geographic atrophy from first diagnosis to end of life;Colijn;JAMA Ophthalmol,2021
3. Consensus definition for atrophy associated with age-related macular degeneration on OCT: classification of atrophy report 3;Sadda;Ophthalmology,2018
4. The effect of pegcetacoplan treatment on photoreceptor maintenance in geographic atrophy monitored by artificial intelligence-based OCT analysis;Riedl;Ophthalmol Retina,2022
5. Association of complement C3 inhibitor pegcetacoplan with reduced photoreceptor degeneration beyond areas of geographic atrophy;Pfau;Sci Rep.,2022
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Predict and Protect: Evaluating the Double-Layer Sign in Age-Related Macular Degeneration;Ophthalmology and Therapy;2024-08-16
2. The Discrepancy Between Visual Acuity Decline and Foveal Involvement in Geographic Atrophy;Ophthalmology Retina;2024-08
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