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Deep Learning of Retinal Photographs and Atherosclerotic Cardiovascular Disease
Sponsor: Yonsei University
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.
Official title: Prediction of Incident Atherosclerotic Cardiovascular Disease From Retinal Photographs Via Deep Learning
Key Details
Gender
All
Age Range
20 Years - 79 Years
Study Type
OBSERVATIONAL
Enrollment
2400
Start Date
2020-10-11
Completion Date
2029-10-10
Last Updated
2021-02-11
Healthy Volunteers
Yes
Conditions
Locations (1)
Yonsei University College of Medicine
Seoul, South Korea