AIMC Topic: Visual Acuity

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Selecting measures of visual function to classify diabetic retinopathy status: a cross-sectional study.

BMJ open ophthalmology
AIM: To identify combinations of up to three visual function tests with the best performance for classifying diabetic retinopathy (DR) severity stage. To describe in detail the measurements from a comprehensive set of visual function tests. METHODS: ...

Fast and accurate visual acuity prediction based on optical aberrations and machine learning.

Scientific reports
In this work, we propose three machine learning-based methods for predicting visual acuity (VA). Two methods utilize regression trees (LSBoost and XGBoost), and the third employs a neural network that classifies simulated aberrated optotypes as "reco...

Artificial intelligence driven intraocular lens power calculation in extreme axial myopia.

Scientific reports
Accurate intraocular lens (IOL) power calculation is critical in cataract surgery, especially in patients with extreme axial myopia where traditional formulas often yield inaccurate results. This study retrospectively evaluated the accuracy of two AI...

Prediction of long-term uncorrected distance visual acuity in surgically SMILE corrected myopic eyes using machine learning.

BMJ open ophthalmology
BACKGROUND: This study aimed to create machine learning (ML) models to predict the long-term uncorrected distance visual acuity (UDVA) in myopic eyes corrected by small incision lenticule extraction (SMILE).

Impact of AI-quantified fluid dynamics on visual outcomes over 5 years in patients with treatment-naïve nAMD from the FRB! registry.

Scientific reports
To investigate the impact of retinal fluid dynamics on visual outcomes in patients with treatment-naïve neovascular age-related macular degeneration (nAMD) treated in the real world over 5 years using approved AI-based fluid monitoring. Real-world da...

Comparative evaluation of traditional and AI-based intraocular lens power calculation formulas in highly myopic eyes.

BMC ophthalmology
PURPOSE: To assess the accuracy of artificial intelligence (AI)-based intraocular lens (IOL) power calculation formulas compared with traditional methods in highly myopic eyes, and to evaluate their performance across varying axial lengths and cornea...

Mapping the impact: AI-driven quantification of geographic atrophy on OCT scans and its association with visual sensitivity loss.

The British journal of ophthalmology
BACKGROUND/AIMS: To examine the association between artificial intelligence (AI)-driven segmentation of geographic atrophy (GA) on optical coherence tomography (OCT) and visual sensitivity loss quantified by defect-mapping microperimetry, a testing s...

Disorganization of retinal inner layers as an optical coherence tomography biomarker in diabetic retinopathy: A review.

Indian journal of ophthalmology
Diabetic retinopathy is a leading cause of vision impairment globally. Disorganization of the retinal inner layers (DRIL), detected via optical coherence tomography, has emerged as a potential biomarker of disease severity and visual prognosis. This ...

Diabetic retinal disease.

Nature reviews. Disease primers
Diabetic retinopathy is a complication of diabetes mellitus that is clinically characterized by changes in retinal microvasculature. Diabetic retinopathy is now better defined as diabetic retinal disease (DRD), as diabetes mellitus affects not only t...

Advances in machine learning for ABCA4-related retinopathy: segmentation and phenotyping.

International ophthalmology
PURPOSE: Stargardt disease, also called ABCA4-related retinopathy (ABCA4R), is the most common form of juvenile-onset macular dystrophy and yet lacks an FDA approved treatment. Substantial progress has been made through landmark studies like that of ...