OBJECTIVES: To assess the performance of feed-forward back-propagation artificial neural networks (ANNs) in detecting field defects caused by pituitary disease from among a glaucomatous population.
PURPOSE: To train a deep learning (DL) algorithm that quantifies glaucomatous neuroretinal damage on fundus photographs using the minimum rim width relative to Bruch membrane opening (BMO-MRW) from spectral-domain optical coherence tomography (SDOCT)...
PURPOSE: Previous approaches using deep learning (DL) algorithms to classify glaucomatous damage on fundus photographs have been limited by the requirement for human labeling of a reference training set. We propose a new approach using quantitative s...
PURPOSE: To investigate the suitability of multi-scale spatial information in 30o visual fields (VF), computed from a Convolutional Neural Network (CNN) classifier, for early-glaucoma vs. control discrimination.
PURPOSE: To determine whether a machine learning technique called Kalman filtering (KF) can accurately forecast future values of mean deviation (MD), pattern standard deviation, and intraocular pressure for patients with normal tension glaucoma (NTG)...
PURPOSE: We sought to construct and evaluate a deep learning (DL) model to diagnose early glaucoma from spectral-domain optical coherence tomography (OCT) images.
PURPOSE: Global indices of standard automated perimerty are insensitive to localized losses, while point-wise indices are sensitive but highly variable. Region-wise indices sit in between. This study introduces a machine learning-based index for glau...
Biologically inspired deep convolutional neural networks (CNNs), trained for computer vision tasks, have been found to predict cortical responses with remarkable accuracy. However, the internal operations of these models remain poorly understood, and...
Computer methods and programs in biomedicine
Nov 15, 2017
BACKGROUND AND OBJECTIVE: This paper builds different neural network models with simple topologies, having one or two hidden layers which were subsequently employed in the prediction of ocular changes progression in patients with diabetes associated ...
Neural networks : the official journal of the International Neural Network Society
May 24, 2016
Decision-making is a flexible process dependent on the accumulation of various kinds of information; however, the corresponding neural mechanisms are far from clear. We extended a layered model of the frontal eye field to a learning-based model, usin...
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