Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2024 Dec 16:11:1423813.
doi: 10.3389/fmed.2024.1423813. eCollection 2024.

Artificial intelligence and glaucoma: a lucid and comprehensive review

Affiliations
Review

Artificial intelligence and glaucoma: a lucid and comprehensive review

Yu Jin et al. Front Med (Lausanne). .

Abstract

Glaucoma is a pathologically irreversible eye illness in the realm of ophthalmic diseases. Because it is difficult to detect concealed and non-obvious progressive changes, clinical diagnosis and treatment of glaucoma is extremely challenging. At the same time, screening and monitoring for glaucoma disease progression are crucial. Artificial intelligence technology has advanced rapidly in all fields, particularly medicine, thanks to ongoing in-depth study and algorithm extension. Simultaneously, research and applications of machine learning and deep learning in the field of glaucoma are fast evolving. Artificial intelligence, with its numerous advantages, will raise the accuracy and efficiency of glaucoma screening and diagnosis to new heights, as well as significantly cut the cost of diagnosis and treatment for the majority of patients. This review summarizes the relevant applications of artificial intelligence in the screening and diagnosis of glaucoma, as well as reflects deeply on the limitations and difficulties of the current application of artificial intelligence in the field of glaucoma, and presents promising prospects and expectations for the application of artificial intelligence in other eye diseases such as glaucoma.

Keywords: artificial intelligence; diagnosis; glaucoma; optical coherence tomography; screening.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
A general procedure of screening for glaucoma.
Figure 2
Figure 2
OCT in AI for glaucoma diagnosis.

Similar articles

References

    1. Jonas JB, Aung T, Bourne RR, Bron AM, Ritch R, Panda-Jonas S. Glaucoma. Lancet. (2017) 390:2183–93. doi: 10.1016/S0140-6736(17)31469-1 - DOI - PubMed
    1. Ferro Desideri L, Rutigliani C, Corazza P, Nastasi A, Roda M, Nicolo M, et al. . The upcoming role of artificial intelligence (AI) for retinal and glaucomatous diseases. J Opt. (2022) 15:S50–7. doi: 10.1016/j.optom.2022.08.001, PMID: - DOI - PMC - PubMed
    1. Huang X, Raja H, Madadi Y, Delsoz M, Poursoroush A, Kahook MY, et al. . Predicting Glaucoma before onset using a large language model Chatbot. Am J Ophthalmol. (2024) 266:289–99. doi: 10.1016/j.ajo.2024.05.022 - DOI - PMC - PubMed
    1. Wiggs JL, Pasquale LR. Genetics of glaucoma. Hum Mol Genet. (2017) 26:R21–7. doi: 10.1093/hmg/ddx184, PMID: - DOI - PMC - PubMed
    1. Chun YS, Sung KR, Park CK, Kim HK, Yoo C, Kim YY, et al. . Factors influencing vision-related quality of life according to glaucoma severity. Acta Ophthalmol. (2018) 97:13918. doi: 10.1111/aos.13918 - DOI - PubMed

LinkOut - more resources