PURPOSE: To determine whether convolutional neural networks (CNN) can classify the severity of central vision loss using fundus autofluorescence (FAF) images and color fundus images of retinitis pigmentosa (RP), and to evaluate the utility of those i...
In 2017, the Japanese Ophthalmological Society (JOS) created the Japan Ocular Imaging (JOI) registry, a national database of images and clinical data in the field of ophthalmology in Japan. The JOI registry automatically transfers the information sto...
PURPOSE: To assess the performance of machine learning classifiers for prediction of progression of normal-tension glaucoma (NTG) in young myopic patients.
PURPOSE: To investigate the performance of deep convolutional neural networks (DCNNs) for glaucoma discrimination using color fundus images STUDY DESIGN: A retrospective study PATIENTS AND METHODS: To investigate the discriminative ability of 3 DCNNs...