Purpose: To describe the indications, motivations, and outcomes of artificial iris exchange.
Setting: Stein Eye Institute.
Design: Consecutive case series.
Various machine learning techniques have been developed for keratoconus detection and refractive surgery screening. These techniques utilize inputs from a range of corneal imaging devices and are built with automated decision trees, support vector machines, and various types of neural networks. In general, these techniques demonstrate very good differentiation of normal and keratoconic eyes, as well as good differentiation of normal and form fruste keratoconus.
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