Ipp E, Liljenquist D, Bode B, et al. Pivotal Evaluation of an Artificial Intelligence System for Autonomous Detection of Referrable and Vision-Threatening Diabetic Retinopathy. JAMA Netw Open. 2021;4(11):e2134254. Published 2021 …
Clinical Validation Study of an automated DR Screening System against 7-field ETDRS Stereoscopic Reference Standard PURPOSE AND BACKGROUND: Comprehensive clinical validation of an automated diabetic retinopathy (DR) screening system, EyeArt …
Read Study | Download PDF The large scale REtrospective Validation of Eyeart in the REal world (REVERE) study assessed the diagnostic efficacy of the EyeArt system screening for referable diabetic …
Purpose Evaluate an artificial intelligence (AI) system to screen people with diabetes at point-of-care for diabetic retinopathy (DR) including diabetic macular edema (DME). Methods We conducted a prospective multi-center study …
Tufail et.al conducted an independent, observational study of 20,258 consecutive patient visits comparing three automated DR screening systems: EyeArt, Retmarker DR, and iGrading. STUDY CONCLUSIONS: Compared to quality assured manual …
