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Table 5 Model testing results obtained after changing the size of the training data set and using the TR as an input feature

From: Automated classifiers for early detection and diagnosis of retinopathy in diabetic eyes

Size of the training data set 20 healthy eyes 30 healthy eyes 40 healthy eyes
TR vs. FD GCL + IPL (eye/scans) OPL (eye/scans) GCL + IPL (eye/scans) OPL (eye/scans) GCL + IPL (eye/scans) OPL (eye/scans)
TP 49/294 48/288 39/234 39/234 29/174 29/174
FN 5/30 6/36 5/30 5/30 5/30 5/30
TN 35/210 37/222 35/210 36/216 35/210 37/222
FP 8/48 6/36 8/48 7/42 8/48 6/36
PPV 0.86 0.89 0.83 0.85 0.78 0.83
Sensitivity 0.91 0.89 0.89 0.89 0.85 0.85
Specificity 0.81 0.86 0.81 0.84 0.81 0.86
  1. Results of sensitivity, specificity, accuracy, predictive values and positive predictive values obtained for the GCL + IPL complex and OPL when training the Bayesian radial basis function network with 20, 30 and 40 healthy eyes with the total reflectance (TR) and fractal dimension (FD) as the input and target features, respectively.
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