Review evaluates retinal imaging and AI modeling's impact on diagnosing Alzheimer's disease, suggesting implications for pathophysiology.
Objective This is a review article to evaluate clinical evidence for the vascular model of Alzheimer's disease (AD) pathology and elucidate the extent to which retinal imaging with AI modeling can be useful in earlier diagnosis of the condition. Methods I comprehensively reviewed the literature on the current understanding of AD pathology and emerging role of the neurovascular system. I reviewed the evidence for retinal vascular biomarkers that can predict the presence of cognitive impairments seen in AD and AI models that utilize these to diagnose and elucidate pathophysiology for the condition. Results It is found that retinal imaging offers a non‐invasive and cost‐effective way to detect AD‐related neurovascular changes and, when coupled with AI, holds a transformative role in improving screening, diagnostics, and our understanding of the disease. Conclusion There is evidence to suggest that retinal imaging can provide an earlier diagnosis of the condition. This can change the practice by encouraging lifestyle modification as crucial in modifying the progression of the disease.
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Eniola Awodiya (2025) studied this question.
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