Abstract
AbstractArtificial intelligence (AI) has recently evoked tremendous excitement for research in the field of Ophthalmology and glaucoma. One of the areas where AI could come into play relates to the prediction of visual field progression. Currently linear trend‐based analysis is the most widely used method for assessing visual field progression. In the recent years a variety of deep learning based approaches have been proposed to better predict visual field progression. Techniques including archetypal analysis, Gaussian mixture model with expectation maximization and Visual Geometry Group standard deep Convolutional Neural Network (CNN) will be discussed. AI has also been used to study mapping of structure to function in glaucoma. This is of importance because it may be used to reduce the variability of visual field data. Hence it may increase our ability to study functional progression by combining perimetry and OCT data. Moreover, the structure/function relationship has been shown to be an independent risk factor for glaucoma progression.
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