AIMC Topic: Axial Length, Eye
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Research on the correlation between retinal vascular parameters and axial length in children using an AI-based fundus image analysis system.
PloS one
Jun 17, 2025
OBJECTIVE: This study aims to utilize artificial intelligence technology to conduct an in-depth analysis of fundus data from myopic children and adolescents, thoroughly exploring the correlation between retinal vascular parameters and axial length (A...
Network meta-analysis of intraocular lens power calculation formulas based on artificial intelligence in short eyes.
BMC ophthalmology
Apr 18, 2025
PURPOSE: To systematically assess and compare the accuracy of artificial intelligence (AI) -based intraocular lens (IOL) power calculation formulas with traditional IOL formulas in patients with short eye length.
Ocular biometric parameters in Chinese preschool children and physiological axial length growth prediction using machine learning algorithms: a retrospective cross-sectional study.
BMJ open
Dec 20, 2024
OBJECTIVES: To examine the ocular biometric parameters and predict the annual growth rate of the physiological axial length (AL) in Chinese preschool children aged 4-6 years old.
Accuracy of 7 Artificial Intelligence-Based Intraocular Lens Power Calculation Formulas in Extremely Long Caucasian Eyes.
American journal of ophthalmology
Nov 12, 2024
PURPOSE: To compare 7 artificial intelligence (AI)-based intraocular lens (IOL) power calculation formulas in extremely long eyes.
Refraction, Ocular
Lenses, Intraocular
Visual Acuity
White People
Aged
Aged, 80 and over
Male
Middle Aged
Lens Implantation, Intraocular
Myopia, Degenerative
Phacoemulsification
Biometry
Optics and Photonics
Axial Length, Eye
Humans
Artificial Intelligence
Retrospective Studies
Female
Reproducibility of Results
Effect of childhood atropine treatment on adult choroidal thickness using sequential deep learning-enabled segmentation.
Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Oct 6, 2024
PURPOSE: To describe choroidal thickness measurements using a sequential deep learning segmentation in adults who received childhood atropine treatment for myopia control.
Development and validation of a deep learning model to predict axial length from ultra-wide field images.
Eye (London, England)
Dec 15, 2023
BACKGROUND: To validate the feasibility of building a deep learning model to predict axial length (AL) for moderate to high myopic patients from ultra-wide field (UWF) images.
Deep Learning Based Prediction of Myopia Control Effect in Children Treated With Overnight Orthokeratology.
Eye & contact lens
Nov 7, 2023
OBJECTIVES: To develop and validate a deep learning-based model for predicting 12-month axial length (AL) elongation using baseline factors and early corneal topographic changes in children treated with orthokeratology (Ortho-K) and to investigate th...
Deep Learning-based Prediction of Axial Length Using Ultra-widefield Fundus Photography.
Korean journal of ophthalmology : KJO
Feb 9, 2023
PURPOSE: To develop a deep learning model that can predict the axial lengths of eyes using ultra-widefield (UWF) fundus photography.
Refractive outcomes of second-eye adjustment methods on intraocular lens power calculation in second eye.
Clinical & experimental ophthalmology
Sep 30, 2021
BACKGROUND: To investigate the refractive outcomes of second-eye adjustment (SEA) methods in different intraocular lens (IOL) power calculation formulas for second eye following bilateral sequential cataract surgery.
Machine learning prediction of pathologic myopia using tomographic elevation of the posterior sclera.
Scientific reports
Mar 26, 2021
Qualitative analysis of fundus photographs enables straightforward pattern recognition of advanced pathologic myopia. However, it has limitations in defining the classification of the degree or extent of early disease, such that it may be biased by s...
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