Artificial Intelligence and Glaucoma

Sidong Liu, Yuyi You*, Stuart L. Graham

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Glaucoma is a group of optic neuropathies characterized by progressive degeneration of the optic nerve with loss of retinal ganglion cells, resulting in irreversible visual field loss. Currently there is no cure for glaucoma, but successful intraocular pressure control can halt or significantly slow the progression of glaucoma, most effectively if the disease is detected at an early stage. Recent advances in artificial intelligence (AI), especially the advent of deep learning, have shown transformative impact on the healthcare industry. AI has shown potential roles in glaucoma, such as detection of signs of glaucomatous damage, assistance in the clinical diagnosis, and evaluation of disease prognosis. In this chapter, we will first provide an overview of the application of AI in glaucoma with a focus on the deep learning models, and then discuss the clinical and technical challenges of current AI systems. Although the challenges are undeniable, further research will likely accelerate emergence of effective AI based systems for glaucoma in clinical practice.
Original languageEnglish
Title of host publicationArtificial intelligence and ophthalmology
Subtitle of host publicationperks, perils and pitfalls
Place of PublicationSingapore
PublisherSpringer, Springer Nature
Chapter6
Pages75-89
Number of pages15
ISBN (Electronic)9789811606342
ISBN (Print)9789811606335
DOIs
Publication statusPublished - 23 Apr 2021

Publication series

NameCurrent Practices in Ophthalmology
PublisherSpringer
ISSN (Print)2523-3807
ISSN (Electronic)2523-3815

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