1. Use of a Neural Net to Model the Impact of Optical Coherence Tomography Abnormalities on Vision in Age-Related Macular Degeneration

    Use of a Neural Net to Model the Impact of Optical Coherence Tomography Abnormalities on Vision in Age-Related Macular Degeneration

    Purpose To develop a neural network for the estimation of visual acuity from optical coherence tomography (OCT) images of patients with neovascular age related macular degeneration and to demonstrate its use to model the impact of specific controlled OCT changes on vision. Design Artificial Intelligence (neural network) study. Methods We assessed 1400 OCT scans of patients with neovascular age related macular degeneration (AMD). 15 physical features for each eligible OCT as well as patient age were used as input data and corresponding recorded visual acuity as the target data to train, validate and test a supervised neural network. We then ...

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