Deep Learning of Retinal Photographs and Atherosclerotic Cardiovascular Disease

Recruiting now

Conditions studied: Cardiovascular Disease

In brief

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.

Key facts

Study ID
NCT04749927
Run by
Yonsei University
People needed
2400
Starts
2020-10-11
Expected to finish
2029-10-10
Last updated by the study team
2021-02-11

Who can join

Age: 20 and older, up to 79. Sex: any. Healthy volunteers: accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

Trial information comes from ClinicalTrials.gov and is refreshed daily. TrialsForMe does not provide medical care and does not run the studies it lists.