PURPOSE: To evaluate the accuracy of detecting glaucoma visual field defect severity using deep-learning (DL) classifier with an ultrawide-field scanning laser ophthalmoscope.
Studies in health technology and informatics
Jan 1, 2017
This paper proposes an automatic classification method to detect glaucoma in fundus images. The method is based on training a neural network using public image databases. The network used in this paper is the GoogLeNet, adapted for this proposal. The...
PURPOSE: To compare the diagnostic performance of different segmentations of the nerve fiber layer (NFL) thickness measurements using an artificial neural network and to define the optimal number of sectors with best diagnostic ability for glaucoma d...
Investigative ophthalmology & visual science
Jun 1, 2015
PURPOSE: To increase the effectiveness of treating open-angle glaucoma (OAG), we tried to find a screening method of differentiating OAG from glaucoma suspect (GS) without a visual field (VF) test.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2015
Here we introduce artificial intelligence (AI) methodology for detecting and characterizing epistasis in genetic association studies. The ultimate goal of our AI strategy is to analyze genome-wide genetics data as a human would using sources of exper...