AIMC Topic: Refraction, Ocular

Clear Filters Showing 11 to 20 of 57 articles

Artificial intelligence in the diagnosis and management of refractive errors.

European journal of ophthalmology
Refractive error is among the leading causes of visual impairment globally. The diagnosis and management of refractive error has traditionally relied on comprehensive eye examinations by eye care professionals, but access to these specialized service...

Accuracy of 7 artificial intelligence-based intraocular lens power calculation formulas in medium-long eyes: 2-center study.

Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
OBJECTIVE: To compare accuracy of 7 artificial intelligence (AI)-based intraocular lens (IOL) power calculation formulas in medium-long eyes DESIGN: Retrospective observational study.

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
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...

Evaluation of prediction errors in nine intraocular lens calculation formulas using an explainable machine learning model.

BMC ophthalmology
BACKGROUND: The purpose of the study was to evaluate the relationship between prediction errors (PEs) and ocular biometric variables in cataract surgery using nine intraocular lens (IOL) formulas with an explainable machine learning model.

Artificial intelligence-assisted fitting method using corneal topography outcomes enhances success rate in orthokeratology lens fitting.

Contact lens & anterior eye : the journal of the British Contact Lens Association
PURPOSE: Based on ideal outcomes of corneal topography following orthokeratology (OK), an innovative machine learning algorithm for corneal refractive therapy (CRT) was developed to investigate the precision of artificial intelligence (AI)-assisted O...

Enhancing Predicted Visual Acuity After SmartSight Lenticule Extraction: Identifying Key Factors With Machine Learning.

Journal of refractive surgery (Thorofare, N.J. : 1995)
PURPOSE: To develop a predictive model aimed at assessing the likelihood of improvement in corrected distance visual acuity (CDVA) for patients undergoing lenticule extraction using the SmartSight system from SCHWIND eye-tech-solutions. This model ev...