0000000000404269
AUTHOR
Frank D. Verbraak
showing 3 related works from this author
Use in clinical practice of an automated screening method of diabetic retinopathy that can be derived using a diagnostic artificial intelligence syst…
2021
Resumen Antecedentes y objetivo Comparar el rendimiento diagnostico de un sistema de inteligencia artificial (IA) de diagnostico autonomo para el diagnostico de retinopatia diabetica derivable (RDR) con la clasificacion manual. Materiales y metodos Sujetos con diabetes tipo 1 y 2 participaron en un programa de cribado de retinopatia diabetica (RD) entre 2011-2012. Se recogieron dos imagenes de cada ojo. Se obtuvieron imagenes retinianas no identificables, una centrada en el disco y otra en la fovea. Los examenes se clasificaron con el sistema de IA autonomo y manualmente por parte de oftalmologos anonimos. Los resultados del sistema de IA y de la clasificacion manual se compararon en cuanto…
Use in clinical practice of an automated screening method of diabetic retinopathy that can be derived using a diagnostic artificial intelligence syst…
2020
Abstract Background and Objective To compare the diagnostic performance of an autonomous diagnostic artificial intelligence (AI) system for the diagnosis of derivable diabetic retinopathy (RDR) with manual classification. Materials and Methods Patients with type 1 and type 2 diabetes participated in a diabetic retinopathy (RD) screening program between 2011–2012. 2 images of each eye were collected. Unidentifiable retinal images were obtained, one centered on the disc and one on the fovea. The exams were classified with th e autonomous AI system and manually by anonymous ophthalmologists. The results of the AI system and manual classification were compared in terms of sensitivity and specif…
Validation of Automated Screening for Referable Diabetic Retinopathy With an Autonomous Diagnostic Artificial Intelligence System in a Spanish Popula…
2020
Purpose: The purpose of this study is to compare the diagnostic performance of an autonomous artificial intelligence (AI) system for the diagnosis of referable diabetic retinopathy (RDR) to manual grading by Spanish ophthalmologists. Methods: Subjects with type 1 and 2 diabetes participated in a diabetic retinopathy (DR) screening program in 2011 to 2012 in Valencia (Spain), and two images per eye were collected according to their standard protocol. Mydriatic drops were used in all patients. Retinal images—one disc and one fovea centered—were obtained under the Medical Research Ethics Committee approval and de-identified. Exams were graded by the autonomous AI system (IDx-DR, Coralville, Io…