AI facial-photo screening for coronary artery disease in high-risk community members
Official title: AI Facial Analysis Algorithm to Screening Coronary Artery Disease in High-Risk Community Population
Run by China National Center for Cardiovascular Diseases · NCT07277686 · Data updated 2026-11-12
This project tests whether an AI algorithm can use a facial photo to screen for coronary artery disease in people with diabetes, high blood pressure, or over age 65.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 1392 (estimated) |
| Sponsor | China National Center for Cardiovascular Diseases Government |
| Locations | 3 sites (Zhoukou, Henan and 2 other locations) |
| Status | Recruiting |
| Started | December 11, 2025 |
| Main results expected | April 1, 2026 |
| Study ends | August 1, 2026 |
| Registry record updated | January 6, 2026 |
| Trial ID | NCT07277686 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults aged 18 or older who live in the participating communities, have diabetes, hypertension, or are older than 65, and who do not have prior CAD or heart failure and can have clear facial photos taken.
✕Probably not a fit
People with a prior diagnosis of coronary artery disease or heart failure, those with major facial surgery or severe facial trauma, or those who refuse participation are unlikely to benefit from this screening approach.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study will use an AI algorithm to analyze standardized facial images from community-dwelling adults at high risk for coronary artery disease (those with diabetes, hypertension, or aged >65). Participants without prior CAD or heart failure will have facial photographs taken and their AI-assigned risk will be compared to actual CAD prevalence in high- versus low-risk groups. The study will also compare the CAD detection rate using the AI screening strategy to the natural detection rate observed in the real-world cohort. Enrollment and data collection occur at participating hospitals in Zhoukou, Henan and at Fuwai Hospital/CAMS in Beijing.
Why it matters
Potential benefit: If successful, this method could provide a low-cost, noninvasive way to identify people at higher risk of coronary artery disease in community settings.
How similar studies have gone: Facial-image AI for cardiovascular risk is a relatively new approach with limited prior validation, although early pilot work has suggested facial features may correlate with cardiovascular risk factors.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Age \>= 18 years. * Community high-risk population, defined as individuals meeting at least one of the following criteria: 1. Diagnosed with Diabetes Mellitus; 2. Diagnosed with Hypertension; 3. Advanced age (\> 65 years old). Exclusion Criteria: * Prior confirmed diagnosis of Coronary Heart Disease (CAD), including clinically diagnosed CAD, history of Coronary Artery Bypass Grafting (CABG), or history of Percutaneous Coronary Intervention (PCI). * History of diagnosed Heart Failure. * Significant facial alterations or conditions that may interfere with AI image analysis, such as plastic surgery, severe facial trauma, or heavy makeup. * Refusal to participate in the study.
Where it's running
-
Zhoukou Chuanhui District Hospital of Traditional Chinese Medicine
Zhoukou, Henan, China Recruiting -
Zhoukou Specialized Disease Hospital
Zhoukou, Henan, China Recruiting -
Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
Beijing, China Not yet recruiting
Study contacts
- Study coordinator: zhe zheng, MD, PhD
- Email: zhengzhe@fuwai.com
- Phone: +86-010-88398027
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.