AI Medical Compendium Journal:
The British journal of ophthalmology

Showing 21 to 30 of 77 articles

Prediction of visual field progression with serial optic disc photographs using deep learning.

The British journal of ophthalmology
AIM: We tested the hypothesis that visual field (VF) progression can be predicted with a deep learning model based on longitudinal pairs of optic disc photographs (ODP) acquired at earlier time points during follow-up.

Automated classification of multiple ophthalmic diseases using ultrasound images by deep learning.

The British journal of ophthalmology
BACKGROUND: Ultrasound imaging is suitable for detecting and diagnosing ophthalmic abnormalities. However, a shortage of experienced sonographers and ophthalmologists remains a problem. This study aims to develop a multibranch transformer network (MB...

Approved AI-based fluid monitoring to identify morphological and functional treatment outcomes in neovascular age-related macular degeneration in real-world routine.

The British journal of ophthalmology
AIM: To predict antivascular endothelial growth factor (VEGF) treatment requirements, visual acuity and morphological outcomes in neovascular age-related macular degeneration (nAMD) using fluid quantification by artificial intelligence (AI) in a real...

Deep learning detection of diabetic retinopathy in Scotland's diabetic eye screening programme.

The British journal of ophthalmology
BACKGROUND/AIMS: Support vector machine-based automated grading (known as iGradingM) has been shown to be safe, cost-effective and robust in the diabetic retinopathy (DR) screening (DES) programme in Scotland. It triages screening episodes as gradabl...

Prediction of retinopathy progression using deep learning on retinal images within the Scottish screening programme.

The British journal of ophthalmology
BACKGROUND/AIMS: National guidelines of many countries set screening intervals for diabetic retinopathy (DR) based on grading of the last screening retinal images. We explore the potential of deep learning (DL) on images to predict progression to ref...

Feasibility and acceptance of artificial intelligence-based diabetic retinopathy screening in Rwanda.

The British journal of ophthalmology
BACKGROUND: Evidence on the practical application of artificial intelligence (AI)-based diabetic retinopathy (DR) screening is needed.

Detecting the corneal neovascularisation area using artificial intelligence.

The British journal of ophthalmology
AIMS: To create and assess the performance of an artificial intelligence-based image analysis tool for the measurement and quantification of the corneal neovascularisation (CoNV) area.

Autonomous screening for laser photocoagulation in fundus images using deep learning.

The British journal of ophthalmology
BACKGROUND: Diabetic retinopathy (DR) is a leading cause of blindness in adults worldwide. Artificial intelligence (AI) with autonomous deep learning algorithms has been increasingly used in retinal image analysis, particularly for the screening of r...

Deep-learning automated quantification of longitudinal OCT scans demonstrates reduced RPE loss rate, preservation of intact macular area and predictive value of isolated photoreceptor degeneration in geographic atrophy patients receiving C3 inhibition treatment.

The British journal of ophthalmology
OBJECTIVE: To evaluate the role of automated optical coherence tomography (OCT) segmentation, using a validated deep-learning model, for assessing the effect of C3 inhibition on the area of geographic atrophy (GA); the constituent features of GA on O...