
Two studies reviewed here successfully developed AI-based algorithms for automating the segmentation and quantification of retinoschisis cavity volume in X-linked retinoschisis (XLRS) patients using OCT images. AI analytics matched or exceeded human performance and, in clinical trial simulations, AI-quantified schisis volume (ASV) proved a better structural endpoint than CST or CFT. These results support AI-driven cavity measurement as a promising tool for XLRS therapeutic trials.
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