Ophthalmology

Corneal Topography Raw Data Classification Using a Convolutional Neural Network.

PURPOSE: We investigated the efficiency of a convolutional neural network applied to corneal topography raw data to classify examinations of 3 categories: normal, keratoconus (KC), and history of refractive surgery (RS).

Automated diagnoses of age-related macular degeneration and polypoidal choroidal vasculopathy using bi-modal deep convolutional neural networks.

AIMS: To investigate the efficacy of a bi-modality deep convolutional neural network (DCNN) framework to categorise age-related macular degeneration (AMD) and polypoidal choroidal vasculopathy (PCV) from colour fundus images and optical coherence tomography (OCT) images.

Safety and efficacy of subcutaneous alpha-tocopherol in healthy adult horses.

Vitamin E is essential for neuromuscular function. The primary treatment, oral supplementation with natural ('RRR') α-tocopherol, is not effective in ...

An innovative method for screening and evaluating the degree of diabetic retinopathy and drug treatment based on artificial intelligence algorithms.

Current methods of evaluating the degree of diabetic retinopathy are highly subjective and have no quantitative standard. To objectively evaluate the ...

S100 proteins, cytokines, and chemokines as tear biomarkers in children with juvenile idiopathic arthritis-associated uveitis.

PURPOSE: Biomarkers for juvenile idiopathic arthritis-associated uveitis (JIA-U) are needed. We aimed to measure inflammatory biomarkers in tears as a...

Big Data Driven Detection of Trees in Suburban Scenes Using Visual Spectrum Eye Level Photography.

The aim of the work described in this paper is to detect trees in eye level view images. Unlike previous work that universally considers highly constr...

Applications of Artificial Intelligence in the Screening of Glaucoma in China.

Deep learning architectures analysis for age-related macular degeneration segmentation on optical coherence tomography scans.

BACKGROUND AND OBJECTIVES: Aged people usually are more to be diagnosed with retinal diseases in developed countries. Retinal capillaries leakage into...

Detection of Intestinal Protozoa in Trichrome-Stained Stool Specimens by Use of a Deep Convolutional Neural Network.

Intestinal protozoa are responsible for relatively few infections in the developed world, but the testing volume is disproportionately high. Manual li...

A Modeling Study of the Emergence of Eye Position Gain Fields Modulating the Responses of Visual Neurons in the Brain.

The responses of many cortical neurons to visual stimuli are modulated by the position of the eye. This form of gain modulation by eye position does n...

WGAN domain adaptation for the joint optic disc-and-cup segmentation in fundus images.

PURPOSE: The cup-to-disc ratio (CDR), a clinical metric of the relative size of the optic cup to the optic disc, is a key indicator of glaucoma, a chr...

Deep Learning Automated Detection of Reticular Pseudodrusen from Fundus Autofluorescence Images or Color Fundus Photographs in AREDS2.

PURPOSE: To develop deep learning models for detecting reticular pseudodrusen (RPD) using fundus autofluorescence (FAF) images or, alternatively, colo...

Fully Automated Segmentation of Globes for Volume Quantification in CT Images of Orbits using Deep Learning.

BACKGROUND AND PURPOSE: Fast and accurate quantification of globe volumes in the event of an ocular trauma can provide clinicians with valuable diagno...

Applying Machine Learning to Kinematic and Eye Movement Features of a Movement Imitation Task to Predict Autism Diagnosis.

Autism is a developmental condition currently identified by experts using observation, interview, and questionnaire techniques and primarily assessing...

Predicting conversion to wet age-related macular degeneration using deep learning.

Progression to exudative 'wet' age-related macular degeneration (exAMD) is a major cause of visual deterioration. In patients diagnosed with exAMD in ...

Commentary: Robotic-Re-Thymectomy: A Surgical Effective Chance to Treat Refractory Myasthenia Gravis.

EEG Signal and Feature Interaction Modeling-Based Eye Behavior Prediction Research.

In recent years, with the development of brain science and biomedical engineering, as well as the rapid development of electroencephalogram (EEG) sign...

Automatic Grading System for Diabetic Retinopathy Diagnosis Using Deep Learning Artificial Intelligence Software.

: To describe the development and validation of an artificial intelligence-based, deep learning algorithm (DeepDR) for the detection of diabetic retin...

AxoNet: A deep learning-based tool to count retinal ganglion cell axons.

In this work, we develop a robust, extensible tool to automatically and accurately count retinal ganglion cell axons in optic nerve (ON) tissue images...

The usefulness of the Deep Learning method of variational autoencoder to reduce measurement noise in glaucomatous visual fields.

The aim of the study was to investigate the usefulness of processing visual field (VF) using a variational autoencoder (VAE). The training data consis...