Extended Data Fig. 7: Performance of the detection model under blurring, brightness, color, and noise adjustment gradients.
From: Early detection of visual impairment in young children using a smartphone-based deep learning system
a, Cartoon diagram showing adjusting effect on the input data by blurring factors. b, Cartoon diagram showing adjusting effect on the input data by brightness factors. c, Cartoon diagram showing adjusting effect on the input data by color factors. d, Cartoon diagram showing adjusting effect on the input data by noise factors. e, ROC curves of the detection model for identifying visual impairment change by blurring factors (AUCs range from 0.683 for factor 37 to 0.951 for factor 0). f, ROC curves of the detection model for identifying visual impairment change by brightness factors (AUCs range from 0.551 for factor 0.9 to 0.951 for factor 0). g, ROC curves of the detection model for identifying visual impairment change by color factors (AUCs range from 0.930 for factor 70 to 0.952 for factor 20). h, ROC curves of the detection model for identifying visual impairment change by noise factors (AUCs range from 0.820 for factor 1800 to 0.951 for factor 0). NI, n = 60; VI, n = 140; ROC curve, receiver operating characteristic curve; VI, visual impairment; NI, nonimpairment.
