Publications
Learn more about our recent studies in using AI deep-learning models, Reti-Intelligence to detect a range of health conditions.
Big data and artificial intelligence in ophthalmology
Frontiers in Medicine, February 2023 Editorial on the Research Topic Big Data and Artificial Intelligence (AI) are rapidly transforming modern healthcare. The combination of these technologies...
Artificial Intelligence in Predicting Systemic Disease from Ocular Imaging
Digital Eye Care and Teleophthalmology | June 20, 2023 Abstract Artificial Intelligence (AI) has diverse applications in modern health care. Deep learning (DL) systems in ophthalmology have been...
Non-invasive chronic kidney disease risk stratification tool derived from retina-based deep learning and clinical factors
Nature | npj Digital Medicine, June 2023 Abstract Despite the importance of preventing chronic kidney disease (CKD), predicting high-risk patients who require active intervention is challenging,...
Cardiovascular disease risk assessment using a deep-learning-based retinal biomarker: a comparison with existing risk scores
European Heart Journal - Digital Health, April 2023 Aims This study aims to evaluate the ability of a deep-learning-based cardiovascular disease (CVD) retinal biomarker, Reti-CVD,to identify...
Validation of a deep-learning-based retinal biomarker (Reti-CVD) in the prediction of cardiovascular disease: data from UK Biobank
BMC Medicine, January 2023 Background Currently in the United Kingdom, cardiovascular disease (CVD) risk assessment is based on the QRISK3 score, in which 10% 10-year CVD risk indicates clinical...
Predictive, preventive, and personalized management of retinal fluid via computer-aided detection app for optical coherence tomography scans
EPMA Journal, November 2022 Aims Computer-aided detection systems for retinal fluid could be beneficial for disease monitoring and management by chronic age-related macular degeneration (AMD) and...
Validation of deep-learning-based retinal biomarker (Reti-CVD) in the prediction of cardiovascular disease: data from US AREDS
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...
Validation of a deep-learning-based retinal biomarker (RetiCVD) in the prediction of cardiovascular disease: data from UK Biobank
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...
Pivotal trial of a deep-learning-based retinal biomarker (Reti-CVD) in the prediction of cardiovascular disease: data from CMERC-HI
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...
Retinal Photograph-based Deep Learning Predicts CKD among people with preserved kidney function
ASN Kidney Week Abstract, November 2022 Background Predicting kidney disease is challenging, especially in people with preserved kidney function. We developed a novel machine learning based risk...
Artificial Intelligence in Predicting Systemic Parameters and Diseases From Ophthalmic Imaging
Frontiers in Digital Health, May 2022 Artificial Intelligence (AI) analytics has been used to predict, classify, and aid clinical management of multiple eye diseases. Its robust performances have...
Retinal photograph-based deep learning predicts biological age and stratifies morbidity and mortality risk
Age and Ageing, April 2022 Background Ageing is an important risk factor for a variety of human pathologies. Biological age (BA) may better capture aging-related physiological changes compared with...