Deep Learning of Retinal Photographs and Atherosclerotic Cardiovascular Disease
Condition(s) studied
Study summary
The research team has developed a deep learning algorithm that predicts anthropometric factors from fundus photographs and an algorithm that predicts cardiovascular disease risk. Fundus photographs are taken for various cardiovascular diseases (myocardial infarction, heart failure, hypertension with target organ damage, high-risk dyslipidemia, diabetic patients, and low-risk hypertension patients), and a deep learning algorithm for predicting developed anthropometric factors will be validated. Fundus photographs will also be taken twice in the first year, and additional fundus photographs will be taken two years later. Major cardiovascular events will be followed up for 5 years to verify the deep learning algorithm predicting cardiovascular disease risk prospectively.
Eligibility
Primary outcome measure(s)
- Major adverse cardiovascular disease — 4 years
Composite of myocardial infarction, stroke, coronary revascularization including percutaneous coronary intervention and coronary bypass graft, and hospitalization for heart failure
Trial sites (1)
| Facility | City | Region | Status |
|---|---|---|---|
| Yonsei University College of Medicine | Seoul | South Korea | Recruiting |
More Yonsei University trials in South Korea
Other trials for the same condition
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
View NCT04749927 on ClinicalTrials.gov ↗ ← All trials in South Korea