Clinical Study
Glaucoma Diagnostic Accuracy of Machine Learning Classifiers Using Retinal Nerve Fiber Layer and Optic Nerve Data from SD-OCT
Table 4
Areas under the receiver operating characteristic curve (aROCs) of best parameter (BP) and all 23 parameters (AP) obtained with machine learning classifiers and sensitivities (%) with fixed specificities of 80% and 90% for AP.
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MLC: machine learning classifier; aROC: area under the ROC curve; BP: best parameter; AP: all parameters; NP: number of parameters; CI: confidence interval of 95%; BAG: bagging; NB: Naive-Bayes; SVML: linear support vector machine; SVMG: Gaussian support vector machine; MLP: multilayer perceptrons; RBF: radial basis function; RAN: random forest; ENS: ensemble selection; CTREE: classification trees; ADA: AdaBoost. |