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Deep Learning of Retinal Photographs and Atherosclerotic Cardiovascular Disease

Cardiovascular Disease Clinical Trial

Official title:
Prediction of Incident Atherosclerotic Cardiovascular Disease From Retinal Photographs Via Deep Learning

Clinical Trial 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.

Clinical Trial Description

n/a

Study Design

Related Conditions & MeSH terms

Clinical Trial Details
NCT number NCT04749927
Study type Observational
Source Yonsei University
Contact Sungha Park
Phone +82-2228-8460
Email shpark0530@yuhs.ac
Status Recruiting
Phase
Start date October 11, 2020
Completion date October 10, 2029
View Details
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