Publications
Learn more about our recent studies in using AI deep-learning models, Reti-Intelligence to detect a range of health conditions.
Application of a deep-learning marker for morbidity and mortality prediction derived from retinal photographs: a cohort development and validation study
The Lancet Healthy Longevity, Oct. 2024 Summary Background Biological ageing markers are useful to risk stratify morbidity and mortality more precisely than chronological age. In this study, we...
Retinal Imaging and Deep Learning in Predicting All-Cause Mortality among Patients with Cardiovascular Disease: A UK Biobank Study with a Gender Perspective
ARVO Annual Meeting Abstract, June 2024 Abstract Purpose : This Reti-CVD successfully predicted CVD events in individuals with no history of CVD. The present study aims to evaluate the predictive...
Deep learning-based cardiovascular risk stratification for stage 1 hypertension using retinal photographs
ARVO Annual Meeting Abstract, June 2024 Abstract Purpose : The advent of deep learning (DL) algorithms has now made it possible to predict the risk of cardiovascular disease (CVD) using...
Impact of retinal photography-based deep learning system on risk stratification for chronic kidney disease progression
ERA 2024, 23 May 2024 Abstract Background and Aims We had previously developed a deep-learning-based risk evaluation system from retinal photographs, Reti-CKD, for stratifying chronic kidney (CKD)...
Prognostic potentials of AI in ophthalmology: systemic disease forecasting via retinal imaging
Eye and Vision, 06 May 2024 Abstract Background Artificial intelligence (AI) that utilizes deep learning (DL) has potential for systemic disease prediction using retinal imaging. The retina’s unique...
Myopic Maculopathy Analysis Using Multi-task Learning and Pseudo Labeling
Springer International Publishing | Febuary 29, 2024 Abstract With the advent of deep learning, research has achieved significant success in various fields of ophthalmology, such as diabetic...
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 BackgroundWe 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...