Yonsei University College of Medicine
Seoul, 03722, South Korea
Location status: Recruiting
NCT Number: NCT04749927
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.
Interested in participating?
Request Info20 year–79 year
All sexes
Observational
Seoul, 03722, South Korea
Location status: Recruiting
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Time frame: 4 years
Composite of myocardial infarction, stroke, coronary revascularization including percutaneous coronary intervention and coronary bypass graft, and hospitalization for heart failure
Contact information is provided by the study sponsor or research team.
Yonsei University
Other
Prediction of Incident Atherosclerotic Cardiovascular Disease From Retinal Photographs Via Deep Learning
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