AIMS: To construct a program to predict the visual acuity (VA), best corrected VA (BCVA) and spherical equivalent (SE) of patients with retinopathy of prematurity (ROP) from 3 to 12 years old after intravitreal injection (IVI) of anti-vascular endoth...
Neural networks : the official journal of the International Neural Network Society
Oct 16, 2019
Visual development during early childhood is a vital process. Examining the visual acuity of children is essential for early detection of visual abnormalities, but performing visual examination in children is challenging. Here, we developed a human-i...
BACKGROUND: This study is to evaluate the accuracy of machine learning for differentiation between optic neuropathies, pseudopapilledema (PPE) and normals.
Documenta ophthalmologica. Advances in ophthalmology
Jun 11, 2019
PURPOSE: Acuity-VEP approaches basically all use the information obtained across a number of check sizes (or spatial frequencies) to derive a measure of acuity. Amplitude is always used, sometimes combined with phase or a noise measure. In our approa...
In this paper the optimum timing for the postoperative functional cure of basic intermittent exotropia is explored based on support vector machine (SVM). One hundred and thirty-two patients were recruited in this prospective cross-sectional study wit...
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: In this study, we compared deep learning (DL) with support vector machine (SVM), both of which use three-dimensional optical coherence tomography (3D-OCT) images for detecting epiretinal membrane (ERM).
Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
Aug 25, 2018
OBJECTIVE: To report the spectrum of ethambutol induced optic neuropathy in a group of renal patients with tuberculosis and the role of visual evoked response (VER) in evaluating this disorder.
We present a robust deep learning framework for the automatic localisation of cone photoreceptor cells in Adaptive Optics Scanning Light Ophthalmoscope (AOSLO) split-detection images. Monitoring cone photoreceptors with AOSLO imaging grants an excell...