Performance of a deep learning system for detection of referable diabetic retinopathy in real clinical settings. (arXiv:2205.05554v1 [eess.IV])

Background: To determine the ability of a commercially available deep
learning system, RetCAD v.1.3.1 (Thirona, Nijmegen, The Netherlands) for the
automatic detection of referable diabetic retinopathy (DR) on a dataset of
colour fundus images acquired during routine clinical practice in a tertiary
hospital screening program, analyzing the reduction of workload that can be
released incorporating this artificial intelligence-based technology. Methods:
Evaluation of the software was performed on a dataset of 7195 nonmydriatic
fundus images from 6325 eyes of 3189 diabetic …

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