Ru-Ik Chee1, Dana Darwish1, Alvaro Fernandez-Vega1,2,3, Samir Patel2, Karyn Jonas1, Susan Ostmo3, J Peter Campbell3, Michael F Chiang3, Rv Paul Chan1. 1. Department of Ophthalmology and Visual Sciences, Illinois Eye and Ear Infirmary, University of Illinois at Chicago. 2. Department of Ophthalmology, Wills Eye Hospital, Oregon Health & Science University, Portland, OR, United States. 3. Department of Ophthalmology, Casey Eye Institute at Oregon Health & Science University, Portland, OR, United States.
Abstract
PURPOSE OF REVIEW: An update and overview of the literature on current telemedicine applications in retina. RECENT FINDINGS: The application of telemedicine to the field of Ophthalmology and Retina has been growing with advancing technologies in ophthalmic imaging. Retinal telemedicine has been most commonly applied to diabetic retinopathy and retinopathy of prematurity in adult and pediatric patients respectively. Telemedicine has the potential to alleviate the growing demand for clinical evaluation of retinal diseases. Subsequently, automated image analysis and deep learning systems may facilitate efficient processing of large, increasing numbers of images generated in telemedicine systems. Telemedicine may additionally improve access to education and standardized training through tele-education systems. SUMMARY: Telemedicine has the potential to be utilized as a useful adjunct but not a complete replacement for physical clinical examinations. Retinal telemedicine programs should be carefully and appropriately integrated into current clinical systems.
PURPOSE OF REVIEW: An update and overview of the literature on current telemedicine applications in retina. RECENT FINDINGS: The application of telemedicine to the field of Ophthalmology and Retina has been growing with advancing technologies in ophthalmic imaging. Retinal telemedicine has been most commonly applied to diabetic retinopathy and retinopathy of prematurity in adult and pediatric patients respectively. Telemedicine has the potential to alleviate the growing demand for clinical evaluation of retinal diseases. Subsequently, automated image analysis and deep learning systems may facilitate efficient processing of large, increasing numbers of images generated in telemedicine systems. Telemedicine may additionally improve access to education and standardized training through tele-education systems. SUMMARY: Telemedicine has the potential to be utilized as a useful adjunct but not a complete replacement for physical clinical examinations. Retinal telemedicine programs should be carefully and appropriately integrated into current clinical systems.
Entities:
Keywords:
Retina; deep learning; diabetic retinopathy; image analysis; retinopathy of prematurity; telemedicine
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