AIMC Topic: Myopia

Clear Filters Showing 51 to 60 of 94 articles

Automatic Segment and Quantify Choroid Layer in Myopic eyes: Deep Learning based Model.

Seminars in ophthalmology
PURPOSE: To report a rapid and accurate method based upon deep learning for automatic segmentation and measurement of the choroidal thickness (CT) in myopic eyes, and to determine the relationship between refractive error (RE) and CT.

Deep learning for predicting uncorrected refractive error using posterior segment optical coherence tomography images.

Eye (London, England)
BACKGROUND/OBJECTIVES: This study aimed to evaluate a deep learning model for estimating uncorrected refractive error using posterior segment optical coherence tomography (OCT) images.

Generalisability through local validation: overcoming barriers due to data disparity in healthcare.

BMC ophthalmology
Cho et al. report deep learning model accuracy for tilted myopic disc detection in a South Korean population. Here we explore the importance of generalisability of machine learning (ML) in healthcare, and we emphasise that recurrent underrepresentati...

Artificial intelligence-based nomogram for small-incision lenticule extraction.

Biomedical engineering online
BACKGROUND: Small-incision lenticule extraction (SMILE) is a surgical procedure for the refractive correction of myopia and astigmatism, which has been reported as safe and effective. However, over- and under-correction still occur after SMILE. The n...

A method for the automatic detection of myopia in Optos fundus images based on deep learning.

International journal for numerical methods in biomedical engineering
Myopia detection is significant for preventing irreversible visual impairment and diagnosing myopic retinopathy. To improve the detection efficiency and accuracy, a Myopia Detection Network (MDNet) that combines the advantages of dense connection and...

Prediction of Phakic Intraocular Lens Vault Using Machine Learning of Anterior Segment Optical Coherence Tomography Metrics.

American journal of ophthalmology
PURPOSE: To compare the achieved vault using the conventional manufacturer's nomogram and the predicted vault using machine learning, in a large cohort of eyes undergoing posterior chamber phakic intraocular lens (EVO implantable collamer lens [ICL];...

Development and validation of a deep learning system to screen vision-threatening conditions in high myopia using optical coherence tomography images.

The British journal of ophthalmology
BACKGROUND/AIMS: To apply deep learning technology to develop an artificial intelligence (AI) system that can identify vision-threatening conditions in high myopia patients based on optical coherence tomography (OCT) macular images.

Explainable Machine Learning Approach as a Tool to Understand Factors Used to Select the Refractive Surgery Technique on the Expert Level.

Translational vision science & technology
PURPOSE: Recently, laser refractive surgery options, including laser epithelial keratomileusis, laser in situ keratomileusis, and small incision lenticule extraction, successfully improved patients' quality of life. Evidence-based recommendation for ...