AIMC Topic: Myopia
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Ensemble machine learning prediction model for clinical refraction using partial interferometry measurements in childhood.
PloS one
Jul 10, 2025
PURPOSE: To develop an ensemble machine learning prediction model for clinical refraction in childhood using partial interferometry measurements.
Deep learning for predicting myopia severity classification method.
Biomedical engineering online
Jul 9, 2025
BACKGROUND: Myopia is a major cause of vision impairment. To improve the efficiency of myopia screening, this paper proposes a deep learning model, X-ENet, which combines the advantages of depthwise separable convolution and dynamic convolution to cl...
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...
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.
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.
SMOTE-Enhanced Explainable Artificial Intelligence Model for Predicting Visual Field Progression in Myopic Normal Tension Glaucoma.
Journal of glaucoma
Apr 21, 2025
PRCIS: The AI model, enhanced by SMOTE to balance data classes, accurately predicted visual field deterioration in patients with myopic normal tension glaucoma. Using SHAP analysis, the key variables driving disease progression were identified.
Automated Detection of Keratorefractive Laser Surgeries on Optical Coherence Tomography Using Deep Learning.
Journal of refractive surgery (Thorofare, N.J. : 1995)
Mar 1, 2025
PURPOSE: To report a deep learning neural network on anterior segment optical coherence tomography (AS-OCT) for automated detection of different keratorefractive laser surgeries-including laser in situ keratomileusis with femtosecond microkeratome (f...
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...
Machine Learning Approaches in High Myopia: Systematic Review and Meta-Analysis.
Journal of medical Internet research
Jan 3, 2025
BACKGROUND: In recent years, with the rapid development of machine learning (ML), it has gained widespread attention from researchers in clinical practice. ML models appear to demonstrate promising accuracy in the diagnosis of complex diseases, as we...
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