AI-Powered Retina Tracker Revolutionizes Eye Disease Detection in Seconds

Novel AI-powered retina tracker detects eye disease in under one second

The Endocrine SocietyJul 15 2025 A novel AI-powered retina tracker can analyze retinal images with near-perfect accuracy in under one second, according to a study being presented Monday at ENDO 2025, the Endocrine Society's annual meeting in San Francisco, Calif. The researchers say the findings offer hope for sight-saving screenings for diabetic retinopathy and other eye diseases that are fast, affordable, and accessible worldwide. The application, an AI-based model integrated into Simple Mobile AI Retina Tracker (SMART), uses cutting-edge deep learning algorithms to analyze retinal fundus images quickly and accurately, on internet-powered devices including basic smartphones. The SMART AI application enables ophthalmologists to streamline patient screening, empowers primary care providers to incorporate eye exams into routine visits, and expands access to high-quality retinal assessments in regions lacking specialized ophthalmic care." Jansi Rani Sethuraj, B.S.N., R.N., C.C.R.N., presenting author of the University of Texas Health Sciences Center in Houston, Texas Diabetic retinopathy, a leading cause of preventable blindness, affects over 100 million people globally as the incidence and prevalence of diabetes continue to rise worldwide. Two researchers, Ramya Elangovan and Kavin Elangovan of AIM Doctor in Houston, Texas, sourced several thousand anonymized retinal images from multiple datasets representing diverse populations spanning six continents. These images were used to train and validate deep learning models capable of detecting and staging diabetic retinopathy with over 99% accuracy in under one second. The tracker was also able to differentiate diabetic retinopathy from similar eye pathologies. Healthcare professionals from multiple international institutions independently validated the application's reliability and usability, underscoring its global applicability. "By democratizing eye care through universally accessible mobile technology, this innovation has the potential to screen billions globally, reducing vision loss from diabetic retinopathy while transforming healthcare delivery systems," said the chief mentor of this project, Elangovan Krishnan, M.B., B.S., P.G.D.H.M., M.Tech., M.S., Ph.D., of AIM Doctor. "This research proves that AI can be a force for good, bridging gaps in care and bringing hope to millions at risk of losing their sight." The Endocrine Society

AI-powered mobile retina tracker screens for diabetic eye disease with 99% accuracy

A novel AI-powered retina tracker can analyze retinal images with near-perfect accuracy in under one second, according to a study presented at ENDO 2025, the Endocrine Society's annual meeting in San Francisco, Calif. The researchers say the findings offer hope for sight-saving screenings for diabetic retinopathy and other eye diseases that are fast, affordable, and accessible worldwide. "The application, an AI-based model integrated into Simple Mobile AI Retina Tracker (SMART), uses cutting-edge deep learning algorithms to analyze retinal fundus images quickly and accurately, on internet-powered devices including basic smartphones," according to presenting author Jansi Rani Sethuraj, B.S.N., R.N., C.C.R.N., of the University of Texas Health Sciences Center in Houston, Texas. "The SMART AI application enables ophthalmologists to streamline patient screening, empowers primary care providers to incorporate eye exams into routine visits, and expands access to high-quality retinal assessments in regions lacking specialized ophthalmic care." Diabetic retinopathy, a leading cause of preventable blindness, affects over 100 million people globally as the incidence and prevalence of diabetes continue to rise worldwide. Two researchers, Ramya Elangovan and Kavin Elangovan of AIM Doctor in Houston, Texas, sourced several thousand anonymized retinal images from multiple datasets representing diverse populations spanning six continents. These images were used to train and validate deep learning models capable of detecting and staging diabetic retinopathy with over 99% accuracy in under one second. The tracker was also able to differentiate diabetic retinopathy from similar eye pathologies. Health care professionals from multiple international institutions independently validated the application's reliability and usability, underscoring its global applicability. "By democratizing eye care through universally accessible mobile technology, this innovation has the potential to screen billions globally, reducing vision loss from diabetic retinopathy while transforming health care delivery systems," said the chief mentor of this project, Elangovan Krishnan, M.B., B.S., P.G.D.H.M., M.Tech., M.S., Ph.D., of AIM Doctor. "This research proves that AI can be a force for good, bridging gaps in care and bringing hope to millions at risk of losing their sight."