Publications
Learn more about our recent studies in using AI deep-learning models, Reti-Intelligence to detect a range of health conditions.
Deep-Learning-Derived Retinal Cardiovascular Risk Predictor (Reti-CVD) and 14 Cardiovascular Conditions in UK Biobank
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...
Deep Learning-Based Retinal Imaging for Predicting Cardiovascular Disease Events in Prediabetic and Diabetic Patients: A Study Using the UK Biobank
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...
Association Between Atrial Fibrillation and Deep Learning Derived Retinal Features Trained on Electrocardiogram versus Coronary Artery Calcium
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...
Impact of Retinal Photography-Based Deep Learning System on Risk Stratification for CKD Progression
ASN Kidney Week Abstract, November 2023 BACKGROUND We had previously developed a deep-learning-based risk evaluation system from retinal photographs, Reti-CKD, for stratifying chronic kidney...
Pivotal trial of a deep-learning-based retinal biomarker (Reti-CVD) in the prediction of cardiovascular disease: data from CMERC-HI
JAMIA, October 2023 Objective The potential of using retinal images as a biomarker of cardiovascular disease (CVD) risk has gained significant attention, but regulatory approval of such artificial...
Efficacy of deep learning-based artificial intelligence models in screening and referring patients with diabetic retinopathy and glaucoma
Indian J of ophthalmology, August 2023 Purpose To analyze the efficacy of a deep learning (DL)-based artificial intelligence (AI)-based algorithm in detecting the presence of diabetic retinopathy...
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
Springer International Publishing | June 20, 2023 Abstract Artificial Intelligence (AI) has diverse applications in modern health care. Deep learning (DL) systems in ophthalmology have been used to...
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...