AIMC Topic: Visual Acuity
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Artificial intelligence-based extraction of quantitative ultra-widefield fluorescein angiography parameters in retinal vein occlusion.
Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
Aug 31, 2024
OBJECTIVE: To examine the association between quantitative vascular parameters extracted from intravenous fluorescein angiography (IVFA) and baseline clinical characteristics of patients with retinal vein occlusion (RVO).
Disease Activity and Therapeutic Response to Pegcetacoplan for Geographic Atrophy Identified by Deep Learning-Based Analysis of OCT.
Ophthalmology
Aug 14, 2024
PURPOSE: To quantify morphological changes of the photoreceptors (PRs) and retinal pigment epithelium (RPE) layers under pegcetacoplan therapy in geographic atrophy (GA) using deep learning-based analysis of OCT images.
LASIK Versus PRK Based on Increased Risk of Corneal Haze: Assessing Current Decision-Making Capabilities of Six Artificial Intelligence Models in Refractive Surgery.
Journal of refractive surgery (Thorofare, N.J. : 1995)
Aug 1, 2024
PURPOSE: To investigate the current decision-making capabilities of 6 different artificial intelligence (AI) models by assessing their refractive surgery recommendations (laser in-situ keratomileusis [LASIK] or photorefractive keratectomy [PRK]) for ...
Interpretable Machine Learning-Based Risk Score for Predicting 10-Year Corneal Graft Survival After Penetrating Keratoplasty and Deep Anterior Lamellar Keratoplasty in Asian Eyes.
Cornea
Jul 24, 2024
PURPOSE: To predict 10-year graft survival after deep anterior lamellar keratoplasty (DALK) and penetrating keratoplasty (PK) using a machine learning (ML)-based interpretable risk score.
Predicting postoperative visual acuity in epiretinal membrane patients and visualization of the contribution of explanatory variables in a machine learning model.
PloS one
Jul 22, 2024
BACKGROUND: The purpose of this study was to develop a model that can predict the postoperative visual acuity in eyes that had undergone vitrectomy for an epiretinal membrane (ERM). The Light Gradient Boosting Machine (LightGBM) was used to evaluate ...
Establishment of a corneal ulcer prognostic model based on machine learning.
Scientific reports
Jul 12, 2024
Corneal infection is a major public health concern worldwide and the most common cause of unilateral corneal blindness. Toxic effects of different microorganisms, such as bacteria and fungi, worsen keratitis leading to corneal perforation even with o...
Development and evaluation of a deep neural network model for orthokeratology lens fitting.
Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)
Jul 9, 2024
PURPOSE: To optimise the precision and efficacy of orthokeratology, this investigation evaluated a deep neural network (DNN) model for lens fitting. The objective was to refine the standardisation of fitting procedures and curtail subjective evaluati...
Quantitative assessment of colour fundus photography in hyperopia children based on artificial intelligence.
BMJ open ophthalmology
Jul 5, 2024
OBJECTIVES: This study aimed to quantitatively evaluate optic nerve head and retinal vascular parameters in children with hyperopia in relation to age and spherical equivalent refraction (SER) using artificial intelligence (AI)-based analysis of colo...
Comparing the accuracy of intraocular lens power calculation formulas using artificial intelligence and traditional formulas in highly myopic patients: a meta-analysis.
International ophthalmology
Jun 21, 2024
PURPOSE: The accuracy of intraocular lens (IOL) calculations is one of the key indicators for determining the success of cataract surgery. However, in highly myopic patients, the calculation errors are relatively larger than those in general patients...
Predicting Success in Descemet Membrane Endothelial Keratoplasty Using Machine Learning.
Cornea
Jun 20, 2024
PURPOSE: This study aimed to predict early graft failure (GF) in patients who underwent Descemet membrane endothelial keratoplasty based on donor characteristics.
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