Intelligent screening of narrow anterior chamber angle based on portable slit lamp

Primary angle closure glaucoma (PACG) is a major cause of irreversible blindness, characterized by shallow anterior chambers and narrow angles. In our study, we used anterior segment photographs from a modified mobile camera to develop algorithms for identifying narrow anterior chamber angles (NACA). We calculated eight biological parameters after preprocessing the images, segmenting the corneal and iris light bands, and modeling the central anterior chamber. In the training dataset, the accuracy of NACA identification using these parameters ranged from 0.68 to 0.85, with an AUC of 0.76 to 0.90. The internal test dataset's accuracy ranged from 0.65 to 0.85, with sensitivity between 0.40 and 0.95 and specificity between 0.61 and 1.00. An ensemble model achieved a sensitivity of 0.90 and a specificity of 0.85 on the internal test dataset, but its performance declined on external datasets. Despite generalization challenges, portable slit lamps equipped with advanced algorithms show promise for NACA screening.