SCREENING GLAUCOMA IN COLOR FUNDUS IMAGES USING ARTIFICIAL INTELLIGENCE SOFWARE EYEDR (Vietnam Journal of Community Medicine, 2022)
Using Darknet convolutional neural network technology, YOLO version 3 develops an artificialintelligence system called EYEDR, that can screen glaucoma by disc imaging automatically.Purposes: Determining the validity and reliability of the artificial intelligence algorithm EYEDR inthe screening of adult glaucoma by color images of the optic disc.Methods: Cross-sectional study. The 2470 color images of the optic disc were selected to trainmachine learning with Darknet YOLO convolutional neural network to determine the shape of theoptic disc and optic cup, thereby an artificial intelligence algorithm was developed to detect theglaucoma and non-glaucoma optic nerve. A test dataset of 1028 disc images was used to evaluatethe value of this AI software based on the sensitivity, specificity, area under the ROC curve (AUC),likelihood ratio, accuracy, and Cohen’s Kappa coefficient.Results: The area under the curve (AUC) was 0.93 ± 0.01 (95% CI; 0.92 - 0.95), with the sensitivity90.03%, specificity 95.06%, the accuracy 86.8% and the Kappa coefficient 0.86 with p
Keywords: Glaucoma, optic disc, atrificial intelligence.