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The choroid is a densely vascular layer that sustains the outer retina and may reflect systemic microvascular health. With the advent of new imaging techniques, choroidal imaging has become increasingly detailed, generating vast data volumes. Conventional analytic tools often fall short in managing these high-dimensional datasets. Artificial intelligence (AI) automatically enhances, segments, and analyzes choroidal images, facilitating the discovery of choroidal biomarkers relevant to ocular and systemic disease. Yet, anatomical complexity, heterogeneous protocols, and a lack of large, annotated datasets hinder AI adoption. Overcoming these barriers is essential to assess AI-derived choroidal biomarkers as reliable diagnostic and prognostic tools.
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Gagliardi et al. (2026) studied this question.
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