Supplementary Material for: The British-Israeli Project for Algorithm-Based Management of Age-related Macular Degeneration: Deep Learning Integration for Real- World Data Management and Analysis
Version 1Purpose: To describe the development of an integrative dataset, combining clinical and optical coherence tomography (OCT) imaging data by applying a deep learning algorithm for automated, objective, and comprehensive quantification of OCT scans to two large real-world datasets of eyes with neovascular age-related macular degeneration (nAMD). We further report baseline characteristics of the study population, focusing on demographics, clinical parameters, and quantitative retinal morphological fe
No license available
Purpose: To describe the development of an integrative dataset, combining clinical and optical coherence tomography (OCT) imaging data by applying a deep learning algorithm for automated, objective, and comprehensive quantification of OCT scans to two large real-world datasets of eyes with neovascular age-related macular degeneration (nAMD). We further report baseline characteristics of the study population, focusing on demographics, clinical parameters, and quantitative retinal morphological fe