Because of recent advances in computing technology and the availability of large datasets, deep learning has risen to the forefront of artificial intelligence, with performances that often …
A plethora of classification models for the detection of glaucoma from fundus images have been proposed in recent years. Often trained with data from a single glaucoma clinic, they …
Purpose To investigate whether predictions of retinal nerve fiber layer (RNFL) thickness obtained from a deep learning model applied to fundus photographs can detect progressive …
Glaucoma and other optic neuropathies are characterized by progressive dysfunction and loss of retinal ganglion cells and their axons. Given the high prevalence of glaucoma-related …
F Li, D Song, H Chen, J Xiong, X Li, H Zhong… - NPJ digital …, 2020 - nature.com
Abstract By 2040,~ 100 million people will have glaucoma. To date, there are a lack of high- efficiency glaucoma diagnostic tools based on visual fields (VFs). Herein, we develop and …
Purpose: This concise review aims to explore the potential for the clinical implementation of artificial intelligence (AI) strategies for detecting glaucoma and monitoring glaucoma …
Purpose To compare convolutional neural network (CNN) analysis of en face vessel density images to gradient boosting classifier (GBC) analysis of instrument-provided, feature-based …
Since the introduction of artificial intelligence (AI) in 1956 by John McCarthy, the field has propelled medicine, optimized efficiency, and led to technological breakthroughs in clinical …
W ith aging populations, health systems worldwide are struggling to provide adequate eye care at the population level, giving rise to projections of increasing levels of visual …