Deep Learning of Retinal Photographs and Atherosclerotic Cardiovascular Disease - Trial NCT04749927
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Study Focus
Observational
Sponsor & Location
Yonsei University
Timeline & Enrollment
N/A
Oct 11, 2020
Oct 10, 2029
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
Data Source
ClinicalTrials.gov
NCT04749927
Non-Device Trial