AI Facial Image Analysis to Screen for Coronary Artery Disease in Adults at High Risk from Community Settings

What this Trial Is About

Researchers are evaluating a facial image-based artificial intelligence AI algorithm designed to screen for coronary artery disease CAD in high-risk community populations, including those with diabetes, hypertension, or aged over 65. The study aims to verify if the AI can accurately identify high-risk and low-risk groups by comparing the actual CAD prevalence, and to compare the AI screening detection rate with natural detection rates in a real-world cohort. Participants are divided into two groups. One group undergoes AI-based facial image screening followed by Coronary Computed Tomography Angiography CCTA to confirm CAD diagnosis. The other group represents a real-world setting without the AI screening and is observed to track natural CAD detection and major adverse cardiovascular events MACE over a six-month follow-up period. During the study, all participants receive monitoring for six months to assess CAD presence and cardiovascular outcomes, including heart attacks and revascularization procedures. Researchers will measure differences in CAD prevalence between AI-identified risk groups, detection rates of CAD, and the incidence of cardiovascular events and deaths. This follow-up period helps evaluate the AI screenings performance compared to usual detection methods.

AI Facial Analysis Algorithm to Screening Coronary Artery Disease in High-Risk Community Population