Translational vision science & technology
Nov 1, 2023
PURPOSE: This study aims to investigate generalizability of deep learning (DL) models trained on commonly used public fundus images to an instance of real-world data (RWD) for glaucoma diagnosis.
Translational vision science & technology
Nov 1, 2023
PURPOSE: Predict central 10° global and local visual field (VF) measurements from macular optical coherence tomography (OCT) volume scans with deep learning (DL).
Translational vision science & technology
Aug 1, 2023
PURPOSE: Retinopathy of prematurity (ROP) is a sight-threatening vasoproliferative retinal disease affecting premature infants. The detection of plus disease, a severe form of ROP requiring treatment, remains challenging owing to subjectivity, freque...
PURPOSE: The purpose of this study was to perform a systematic review and meta-analysis to synthesize evidence from studies using deep learning (DL) to predict cardiovascular disease (CVD) risk from retinal images.
PURPOSE: To examine deep learning (DL)-based methods for accurate segmentation of geographic atrophy (GA) lesions using fundus autofluorescence (FAF) and near-infrared (NIR) images.
PURPOSE: To develop and train a deep learning-based algorithm for detecting disorganization of retinal inner layers (DRIL) on optical coherence tomography (OCT) to screen a cohort of patients with diabetic retinopathy (DR).
Translational vision science & technology
Jun 1, 2023
PURPOSE: The structural changes measured by optical coherence tomography (OCT) are related to functional changes in visual fields (VFs). This study aims to accurately assess the structure-function relationship and overcome the challenges brought by t...
Translational vision science & technology
Jun 1, 2023
PURPOSE: To explore associations of fundus tessellated density (FTD) and compare characteristics of different fundus tessellation (FT) distribution patterns, based on artificial intelligence technology using deep learning.
Translational vision science & technology
May 1, 2023
PURPOSE: To evaluate a novel deep learning algorithm to distinguish between eyes that may or may not have a graft detachment based on pre-Descemet membrane endothelial keratoplasty (DMEK) anterior segment optical coherence tomography (AS-OCT) images.