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RECRUITING
NCT04749927

Deep Learning of Retinal Photographs and Atherosclerotic Cardiovascular Disease

Sponsor: Yonsei University

View on ClinicalTrials.gov

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

Locations (1)

Yonsei University College of Medicine

Seoul, South Korea