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Sep 30, 2022 · The feasibility of using baseline fundus autofluorescence (FAF) images to predict GA progression with end-to-end deep learning models has been demonstrated.
Nov 21, 2024 · Uncertainty-Aware Geographic Atrophy Progression Prediction from Fundus Autofluorescence. September 2022; Lecture Notes in Computer Science.
Fundus autofluorescence (FAF) imaging has been shown to be helpful in predicting progression of geographic atrophy (GA) secondary to age-related macular ...
Missing: Uncertainty- Aware
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Uncertainty-Aware Geographic Atrophy Progression Prediction from Fundus Autofluorescence · Author Picture Qi Yang. Data Science Imaging, Genentech, Inc, South ...
Predicting geographic atrophy growth rate from fundus autofluorescence images using deep neural networks ... To read the full-text of this research, you can ...
Aug 6, 2022 · To identify disease activity and effects of intravitreal pegcetacoplan treatment on the topographic progression of geographic atrophy (GA) ...
Oct 26, 2020 · The purpose of this study was to summarize and evaluate artificial intelligence (AI) algorithms used in geographic atrophy (GA) diagnostic processes.
Fundus autofluorescence imaging: systematic review of test accuracy ...
www.nature.com › eye › review
Mar 10, 2017 · We conducted a systematic review of the accuracy of fundus autofluorescence (FAF) imaging for diagnosing and monitoring retinal conditions.
Purpose: To systematically compare the prognostic value of multiple shape-descriptive factors in the natural course of the disease.
In this study, a number of sources of epistemic uncertainty have been identified in GA assessment and its progression in fundus autofluorescence images.
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