AIMC Topic: Visual Acuity
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Real-world faricimab switch in France: artificial intelligence-based detection of changes in exudative signs in difficult-to-treat neovascular age-related macular degeneration.
BMJ open ophthalmology
Jun 23, 2025
PURPOSE: Some patients with neovascular age-related macular degeneration (nAMD) have persistent signs of exudation under treatment with intravitreal injections of anti-vascular endothelial growth factor (VEGF) agents. We examined the real-world anato...
Subretinal Fluid
Intravitreal Injections
Fluorescein Angiography
Wet Macular Degeneration
Antibodies, Bispecific
Male
Angiogenesis Inhibitors
Follow-Up Studies
Visual Acuity
Drug Substitution
France
Exudates and Transudates
Tomography, Optical Coherence
Vascular Endothelial Growth Factor A
Retrospective Studies
Female
Aged
Aged, 80 and over
Humans
Artificial Intelligence
Interpretable machine learning models for predicting childhood myopia from school-based screening data.
Scientific reports
Jun 5, 2025
This study assessed the efficacy of various diagnostic indicators and machine learning (ML) models in predicting childhood myopia. A total of 2,365 children aged 5-12 years were included in the study. The participants were exposed to non-cycloplegic ...
Investigation of Short-term Crystalline Lens Positional Shifts Following ICL Implantation Using SS-OCT Integrated With Multi-task Deep Learning.
Journal of refractive surgery (Thorofare, N.J. : 1995)
Jun 1, 2025
PURPOSE: To investigate the tilt and decentration of the crystalline lens shortly after Implantable Collamer Lens (ICL) implantation.
Evaluating anti-VEGF responses in diabetic macular edema: A systematic review with AI-powered treatment insights.
Indian journal of ophthalmology
May 28, 2025
Recent advances in deep learning and machine learning have greatly increased the capabilities of extracting features for evaluating the response to anti VEGF treatment in patients with Diabetic Macular Edema (DME). In this review, we explore how thes...
Adopting machine learning to predict nomogram for small incision lenticule extraction (SMILE).
International ophthalmology
May 5, 2025
PURPOSE: To predict nomogram for small incision lenticule extraction (SMILE) using machine learning technology and preoperative clinical data.
Predicting Visual Acuity after Retinal Vein Occlusion Anti-VEGF Treatment: Development and Validation of an Interpretable Machine Learning Model.
Journal of medical systems
Apr 29, 2025
Accurate prediction of post-treatment visual acuity in macular edema secondary to retinal vein occlusion (RVO-ME) is critical for optimizing anti-VEGF therapy and improving clinical outcomes. While machine learning (ML) has shown promise in ophthalmi...
Developmental coordination disorder and cerebral visual impairment: What is the association?
Research in developmental disabilities
Apr 24, 2025
INTRODUCTION: Children with Developmental Coordination Disorder (DCD) experience impairments beyond motor planning, affecting visual perceptual and visual-motor integration abilities, similar to children with Cerebral Visual Impairment (CVI), making ...
Unsupervised machine learning analysis of optical coherence tomography radiomics features for predicting treatment outcomes in diabetic macular edema.
Scientific reports
Apr 18, 2025
This study aimed to identify distinct clusters of diabetic macular edema (DME) patients with differential anti-vascular endothelial growth factor (VEGF) treatment outcomes using an unsupervised machine learning (ML) approach based on radiomic feature...
Principal Component Analysis
Tomography, Optical Coherence
Macular Edema
Vascular Endothelial Growth Factor A
Treatment Outcome
Cluster Analysis
Unsupervised Machine Learning
Visual Acuity
Radiomics
Male
Middle Aged
Angiogenesis Inhibitors
Humans
Retrospective Studies
Diabetic Retinopathy
Female
Aged
Prediction of Postoperative Macular Hole Status by Automated Preoperative Retinal OCT Analysis: A Narrative Review.
Ophthalmic surgery, lasers & imaging retina
Mar 1, 2025
Optical coherence tomography (OCT) is a non-invasive imaging modality essential for macular hole (MH) management. Artificial intelligence (AI) algorithms could be applied to OCT to garner insights for MH prognosis and outcomes. The objective was to r...
Machine-learning random forest algorithms predict post-cycloplegic myopic corrections from noncycloplegic clinical data.
Optometry and vision science : official publication of the American Academy of Optometry
Feb 24, 2025
SIGNIFICANCE: Machine learning random forest algorithms were used to predict objective refractive outcomes after cycloplegic refraction using noncycloplegic clinical data. A classification model predicted post-cycloplegic myopia and could be useful i...
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