1. Classification Algorithms Based on Anterior Segment Optical Coherence Tomography Measurements for Detection of Angle Closure

    Classification Algorithms Based on Anterior Segment Optical Coherence Tomography Measurements for Detection of Angle Closure

    Objective: A recent study found that a combination of 6 anterior segment optical coherence tomography (ASOCT) parameters (anterior chamber area, volume, and width [ACA, ACV, ACW], lens vault [LV], iris thickness at 750 μm from the scleral spur, and iris cross-sectional area) explain >80% of the variability in angle width. The aim of this study was to evaluate classification algorithms based on ASOCT measurements for the detection of gonioscopic angle closure.Design: Cross-sectional study.Participants: We included 2047 subjects aged ≥50 years.Methods: Participants underwent gonioscopy and ASOCT (Carl Zeiss Meditec, Dublin, CA). Customized software (Zhongshan Angle Assessment Program, Guangzhou ...

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