AIMC Topic: Myopia
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An Intelligent Grading Model for Myopic Maculopathy Based on Long-Tailed Learning.
Translational vision science & technology
Mar 3, 2025
PURPOSE: To develop an intelligent grading model for myopic maculopathy based on a long-tail learning framework, using the improved loss function LTBSoftmax. The model addresses the long-tail distribution problem in myopic maculopathy data to provide...
The Associations Between Myopia and Fundus Tessellation in School Children: A Comparative Analysis of Macular and Peripapillary Regions Using Deep Learning.
Translational vision science & technology
Jan 2, 2025
PURPOSE: To evaluate the refractive differences among school-aged children with macular or peripapillary fundus tessellation (FT) distribution patterns, using fundus tessellation density (FTD) quantified by deep learning (DL) technology.
Prediction of vaults in eyes with vertical implantable collamer lens implantation.
Journal of cataract and refractive surgery
Jan 1, 2025
PURPOSE: To design formulas for predicting postoperative vaults in vertical implantable collamer lens (ICL) implantation and to achieve more precise predictions using machine learning models.
Machine Learning Models for Predicting Cycloplegic Refractive Error and Myopia Status Based on Non-Cycloplegic Data in Chinese Students.
Translational vision science & technology
Aug 1, 2024
PURPOSE: To develop and validate machine learning (ML) models for predicting cycloplegic refractive error and myopia status using noncycloplegic refractive error and biometric data.
An editorial on myopia control, mainly written by ChatGPT.
Optometry and vision science : official publication of the American Academy of Optometry
May 1, 2024
VAULT: vault accuracy using deep learning technology: new image-based artificial intelligence model for predicting implantable collamer lens postoperative vault.
Journal of cataract and refractive surgery
May 1, 2024
PURPOSE: To develop an accurate deep learning model to predict postoperative vault of phakic implantable collamer lenses (ICLs).
Quantitative Assessment of Fundus Tessellated Density in Highly Myopic Glaucoma Using Deep Learning.
Translational vision science & technology
Apr 2, 2024
PURPOSE: To characterize the fundus tessellated density (FTD) in highly myopic glaucoma (HMG) and high myopia (HM) for discovering early signs and diagnostic markers.
[Preliminary study on automatic quantification and grading of leopard spots fundus based on deep learning technology].
[Zhonghua yan ke za zhi] Chinese journal of ophthalmology
Mar 11, 2024
To achieve automatic segmentation, quantification, and grading of different regions of leopard spots fundus (FT) using deep learning technology. The analysis includes exploring the correlation between novel quantitative indicators, leopard spot fund...
ASSOCIATION OF TESSELLATION DENSITY WITH PROGRESSION OF AXIAL LENGTH AND REFRACTION IN CHILDREN: An Artificial Intelligence-Assisted 4-Year Study.
Retina (Philadelphia, Pa.)
Mar 1, 2024
PURPOSE: To investigate fundus tessellation density (TD) and its association with axial length (AL) elongation and spherical equivalent (SE) progression in children.
Fundus Tessellated Density Assessed by Deep Learning in Primary School Children.
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.
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