11월 25, 2024 | AHA Scientific Session Abstract, Uncategorized
AHAㅣ 2024-11-11 Abstract Introduction: Reti-CVD, a novel cardiovascular risk stratification tool derived from deep learning and retinal photography, offers a promising alternative to CT scan-measured Coronary Artery Calcium (CAC) scores in predicting cardiovascular...11월 25, 2024 | AHA Scientific Session Abstract
AHAㅣ 2024-11-11 Abstract Introduction: Cardiovascular disease (CVD) remains the leading cause of mortality globally, necessitating improved risk stratification and preventive strategies. Reti-CVD, a deep learning model, predicts CVD risk by analyzing retinal...11월 25, 2024 | AHA Scientific Session Abstract
AHAㅣ 2024-11-11 Abstract Introduction: Cardiovascular diseases (CVD) are the leading cause of death in developed countries. Coronary artery calcium (CAC) is a clinically validated strong marker of CVD, and previous studies suggest that retinal blood vessels...11월 10, 2023 | AHA Scientific Session Abstract
AHA Scientific Session Abstract, November 2023 Introduction The advent of sophisticated deep learning algorithms has now made it possible to predict the risk of cardiovascular diseases (CVDs) using retinal images. We had previously developed a retina-based deep...11월 10, 2023 | AHA Scientific Session Abstract
AHA Scientific Session Abstract, November 2023 Introduction Our previous work led to developing a deep learning algorithm for retinal images, Reti-CVD, which effectively predicted cardiovascular disease (CVD) events in individuals without CVD history, leveraging...11월 10, 2023 | AHA Scientific Session Abstract
AHA Scientific Session Abstract, November 2023 Introduction This study aimed to assess the ability of a deep learning algorithm, Reti-AF, developed from retinal photos, to predict atrial fibrillation (AF) incidence. Its predictive performance was evaluated using the...