AI-driven multimodal retinal imaging for early detection and risk stratification of vascular and neurodegenerative diseases
Systemic vascular and neurodegenerative disorders are important causes of disability and death worldwide, mainly because of the late stage of diagnosis and the high cost of current screening tools. Artificial intelligence (AI) and multimodal retinal imaging offer a non-invasive and viable approach for early risk stratification and longitudinal monitoring. This review highlights how changes in the retinal vasculature and nerve layers are markers of underlying pathophysiologies related to cardiovascular, metabolic…
AI combined with multimodal retinal imaging provides a non-invasive method for early risk stratification and screening for cardiovascular, metabolic and neurodegenerative disorders using retinal vasculature and nerve layer changes.
AI-assisted retinal analysis faces implementation hurdles including lack of multicenter validation, need for prospective clinical trials, and unresolved data fusion and regulatory requirements.
Clinical translation is limited by need for multicenter validation, prospective trials, data fusion challenges and regulatory frameworks.
Evidence
- Peer-reviewedGraefe's Archive for Clinical and Experimental Ophthalmology2026-05-22
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Truvace Impact Record TRV-2026-0192, v1: “AI-driven multimodal retinal imaging for early detection and risk stratification of vascular and neurodegenerative diseases.” Truvace, 2026-07-13. /record/TRV-2026-0192 (accessed at citation time). sha256 960b16fb94aa7d0e…
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