  Primary open-angle glaucoma (POAG) is a chronic and progressive optic nerve
condition that results in an acquired loss of optic nerve fibers and potential
blindness. The gradual onset of glaucoma results in patients progressively
losing their vision without being consciously aware of the changes. To diagnose
POAG and determine its severity, patients must undergo a comprehensive dilated
eye examination. In this work, we build a framework to rank, compare, and
interpret the severity of glaucoma using fundus images. We introduce a
siamese-based severity ranking using pairwise n-hidden comparisons. We
additionally have a novel approach to explaining why a specific image is deemed
more severe than others. Our findings indicate that the proposed severity
ranking model surpasses traditional ones in terms of diagnostic accuracy and
delivers improved saliency explanations.
