Key result
Retinal AI score accurately identifies high-risk individuals with ~0.95 AUROC and tracks PREVENT score changes.
Why the study?
While retinal AI enables non-invasive CVD screening, its utility for monitoring longitudinal changes remains unverified.
Does a retinal AI score (Dr. Noon CVD) accurately identify high cardiovascular risk and track longitudinal risk changes compared to the PREVENT score in individuals without baseline CVD?
Observational (n=19,829)
Yes
Does a retinal AI score (Dr. Noon CVD) accurately identify high cardiovascular risk and track longitudinal risk changes compared to the PREVENT score in individuals without baseline CVD?
A retinal AI score accurately identifies high cardiovascular risk and tracks longitudinal risk changes, offering a non-invasive tool for CVD risk monitoring.
Supports retinal AI for non-invasive CVD risk tracking in cohorts; leaves open whether it improves outcomes over PREVENT.
Introduction and Objective: While retinal AI enables non-invasive cardiovascular disease (CVD) screening, its utility for monitoring longitudinal changes remains unverified. We validated a retinal AI score (Dr. Noon CVD) in a Korean population and verified progression patterns using the UK Biobank (UKBB). Methods: We analyzed data from the GreenCross (GC) checkup center (Korea, 2022-2024) and the UKBB. Participants free of baseline CVD with ≥2 fundus exams (≥30 days interval) were included. In GC, missing smoking data were imputed as non-smoker if absent across all visits, or the recorded status otherwise. We assessed AI score’s accuracy for high risk (PREVENT score ≥7.5%) and the correlation between changes in AI and PREVENT scores in GC. Annual progression rates were verified in both datasets. Results: 18,084 (GC) and 1,745 (UKBB) participants were included. Dr. Noon CVD achieved an AUROC of 0.950, and longitudinal score changes correlated strongly with PREVENT changes (r=0.67, p<0.001) in GC. Median annual progression in low-risk (<31) groups was 1.21 [IQR -0.49-3.81] (GC) and 2.03 [1.02-3.62] points/year (UKBB). Rapid progression cutoffs (top 5%) were 16.70 and 5.37 points/year, respectively. Conclusion: Dr. Noon CVD accurately identifies high-risk individuals and effectively tracks dynamic risk changes. The longitudinal progression patterns, verified across Korean and UK populations, support its utility for non-invasive risk monitoring. Disclosure D. Nam: Employee; Current; Mediwhale Inc. J. Seo: Employee; Current; Mediwhale Inc. S. Thakur: Employee; Current; Mediwhale Inc. S. Nusinovici: Consultant; Current; Mediwhale Inc. M. Jang: Employee; Current; Mediwhale Inc. T.H. Rim: Stock/Shareholder; Current; Mediwhale Inc.
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Nam et al. (2026) conducted an observational in Cardiovascular disease risk (n=19,829). Retinal AI score (Dr. Noon CVD) was evaluated on Accuracy for high risk (PREVENT score ≥7.5%) and correlation between changes in AI and PREVENT scores (AUROC 0.950, r=0.67, p=<0.001). The Dr. Noon CVD retinal AI score accurately identified high-risk individuals (AUROC 0.950) and its longitudinal changes correlated strongly with PREVENT score changes (r=0.67, p<0.001).
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