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...
[Zhonghua yan ke za zhi] Chinese journal of ophthalmology
34098696
Choroidal thinning is an important feature of high myopia and has a negative correlation with the degree of myopia. However, due to the limitations of choroidal imaging, specific changes in choroidal thickness and vasculature are unclear. In recent y...
PURPOSE OF REVIEW: Myopia is one of the leading causes of visual impairment, with a projected increase in prevalence globally. One potential approach to address myopia and its complications is early detection and treatment. However, current healthcar...
BACKGROUND/OBJECTIVES: This study aimed to evaluate a deep learning model for estimating uncorrected refractive error using posterior segment optical coherence tomography (OCT) images.
PURPOSE: The purpose of this study was to engineer deep learning (DL) models that can identify myopic maculopathy in patients with high myopia based on optical coherence tomography (OCT) images.
PURPOSE: The purpose of this study was to analyze the choroidal sublayer morphologic features in emmetropic and myopic children using an automatic segmentation model, and to explore the relationship between choroidal sublayers and spherical equivalen...
PURPOSE: Given the robust effectiveness of inhibiting myopia progression, orthokeratology has gained increasing popularity worldwide. However, identifying the boundary and the center of reshaped corneal area (i.e., treatment zone) is the main challen...
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.
Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
34937047
PURPOSE: It is common for physicians to be uncertain when examining some images. Models trained with human uncertainty could be a help for physicians in diagnosing pathologic myopia.