NCT04749927

Deep Learning of Retinal Photographs and Atherosclerotic Cardiovascular Disease

Prediction of Incident Atherosclerotic Cardiovascular Disease From Retinal Photographs Via Deep Learning
Yonsei University·ClinicalTrials.govRecruiting
View on ClinicalTrials.gov
Study focus
Disease/Condition
Cardiovascular Disease
Study type
Observational
Sponsor & location
Primary sponsor
Yonsei University
Location
Seoul, South Korea
Timeline & enrollment
Phase
N/A
Start date
Oct 11, 2020
End date
Oct 10, 2029
Enrollment
2400 participants
Primary outcome

Major adverse cardiovascular disease

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.

ICD-10 classifications
Cardiovascular disease, unspecifiedHypertensive heart diseaseHeart disease, unspecifiedAtherosclerotic cardiovascular disease, so describedAtherosclerotic heart disease
Data source
Registry
ClinicalTrials.gov
Trial ID
NCT04749927
Type
Non-Device Trial
About this record

Access comprehensive clinical trial information for NCT04749927 through Pure Global AI's free database. This phase not specified trial is sponsored by Yonsei University and is currently Recruiting. The study focuses on Cardiovascular Disease. Target enrollment is 2400 participants.

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