Dinesh V Gunasekeran1,2, Daniel S W Ting1,3, Gavin S W Tan1,3, Tien Y Wong1,3. 1. Singapore Eye Research Institute, Singapore National Eye Center. 2. Yong Loo Lin School of Medicine, National University of Singapore. 3. Duke-NUS Medical School, Singapore.
Abstract
PURPOSE OF REVIEW: Diabetic retinopathy is the most common specific complication of diabetes mellitus. Traditional care for patients with diabetes and diabetic retinopathy is fragmented, uncoordinated and delivered in a piecemeal nature, often in the most expensive and high-resource tertiary settings. Transformative new models incorporating digital technology are needed to address these gaps in clinical care. RECENT FINDINGS: Artificial intelligence and telehealth may improve access, financial sustainability and coverage of diabetic retinopathy screening programs. They enable risk stratifying patients based on individual risk of vision-threatening diabetic retinopathy including diabetic macular edema (DME), and predicting which patients with DME best respond to antivascular endothelial growth factor therapy. SUMMARY: Progress in artificial intelligence and tele-ophthalmology for diabetic retinopathy screening, including artificial intelligence applications in 'real-world settings' and cost-effectiveness studies are summarized. Furthermore, the initial research on the use of artificial intelligence models for diabetic retinopathy risk stratification and management of DME are outlined along with potential future directions. Finally, the need for artificial intelligence adoption within ophthalmology in response to coronavirus disease 2019 is discussed. Digital health solutions such as artificial intelligence and telehealth can facilitate the integration of community, primary and specialist eye care services, optimize the flow of patients within healthcare networks, and improve the efficiency of diabetic retinopathy management.
PURPOSE OF REVIEW: Diabetic retinopathy is the most common specific complication of diabetes mellitus. Traditional care for patients with diabetes and diabetic retinopathy is fragmented, uncoordinated and delivered in a piecemeal nature, often in the most expensive and high-resource tertiary settings. Transformative new models incorporating digital technology are needed to address these gaps in clinical care. RECENT FINDINGS: Artificial intelligence and telehealth may improve access, financial sustainability and coverage of diabetic retinopathy screening programs. They enable risk stratifying patients based on individual risk of vision-threatening diabetic retinopathy including diabetic macular edema (DME), and predicting which patients with DME best respond to antivascular endothelial growth factor therapy. SUMMARY: Progress in artificial intelligence and tele-ophthalmology for diabetic retinopathy screening, including artificial intelligence applications in 'real-world settings' and cost-effectiveness studies are summarized. Furthermore, the initial research on the use of artificial intelligence models for diabetic retinopathy risk stratification and management of DME are outlined along with potential future directions. Finally, the need for artificial intelligence adoption within ophthalmology in response to coronavirus disease 2019 is discussed. Digital health solutions such as artificial intelligence and telehealth can facilitate the integration of community, primary and specialist eye care services, optimize the flow of patients within healthcare networks, and improve the efficiency of diabetic retinopathy management.
Authors: Jacqueline Ramke; Jennifer R Evans; Esmael Habtamu; Nyawira Mwangi; Juan Carlos Silva; Bonnielin K Swenor; Nathan Congdon; Hannah B Faal; Allen Foster; David S Friedman; Stephen Gichuhi; Jost B Jonas; Peng T Khaw; Fatima Kyari; Gudlavalleti V S Murthy; Ningli Wang; Tien Y Wong; Richard Wormald; Mayinuer Yusufu; Hugh Taylor; Serge Resnikoff; Sheila K West; Matthew J Burton Journal: Lancet Healthy Longev Date: 2022-01