Nov 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...Nov 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...Nov 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...Nov 16, 2022 | AHA Scientific Session Abstract
AHA Scientific Session Abstract, November 2022 Background In our previous study, we developed a deep-learning-based novel cardiovascular disease (CVD) risk stratification system based on retinal photographs, Reti-CVD. This study aims to further validate Reti-CVD in...Nov 16, 2022 | AHA Scientific Session Abstract
AHA Scientific Session Abstract, November 2022 Introduction Currently in the United Kingdom, cardiovascular disease (CVD) risk assessment is based on the QRISK3 score, with a benchmark of 10% for 10-year CVD risk determining clinical intervention. Yet, effects on...Nov 16, 2022 | AHA Scientific Session Abstract
AHA Scientific Session Abstract, November 2022 Introduction The Korean Ministry of Food and Drug Safety (K-MFDS) has authorized over 110 artificial intelligence (AI)-software as medical devices (AI-SaMDs) for diagnostic purposes. Herein, we clinically validate the...