Analysis of glaucoma diagnosis with automated classifiers using Stratus optical coherence tomography

摘要

The study compared the performances of two classification methods including logistic regression analysis and artificial neural network (ANN) in terms of the area under the receiver operating characteristic curves for differentiating glaucomatous from normal eyes in Taiwan Chinese population based solely on the quantitative assessment of summary data reports from the Stratus optical coherence tomography (OCT). The logistic regression analysis and ANNs showed promise for increasing diagnostic accuracy of glaucoma using summary data from Stratus OCT. The results can be used as the basis for further improving the diagnostic accuracy of glaucoma.