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人工智能与青光眼:一篇清晰且全面的综述

Artificial intelligence and glaucoma: a lucid and comprehensive review.

作者信息

Jin Yu, Liang Lina, Li Jiaxian, Xu Kai, Zhou Wei, Li Yamin

机构信息

Department of Eye Function Laboratory, Eye Hospital, China Academy of Chinese Medical Sciences, Beijing, China.

出版信息

Front Med (Lausanne). 2024 Dec 16;11:1423813. doi: 10.3389/fmed.2024.1423813. eCollection 2024.


DOI:10.3389/fmed.2024.1423813
PMID:39736974
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11682886/
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.

摘要

青光眼是眼科疾病领域中一种病理上不可逆的眼部疾病。由于难以检测出隐蔽且不明显的渐进性变化,青光眼的临床诊断和治疗极具挑战性。与此同时,对青光眼疾病进展的筛查和监测至关重要。得益于持续深入的研究和算法扩展,人工智能技术在各个领域,尤其是医学领域取得了飞速发展。同时,机器学习和深度学习在青光眼领域的研究与应用也在迅速发展。人工智能凭借其众多优势,将把青光眼筛查和诊断的准确性和效率提升到新高度,同时大幅降低大多数患者的诊断和治疗成本。本文综述了人工智能在青光眼筛查和诊断中的相关应用,深入思考了当前人工智能在青光眼领域应用的局限性和困难,并对人工智能在青光眼等其他眼部疾病中的应用展现出了广阔前景和期望。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dd4/11682886/e228998eaab3/fmed-11-1423813-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dd4/11682886/4dd1e7b05fc3/fmed-11-1423813-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dd4/11682886/e228998eaab3/fmed-11-1423813-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dd4/11682886/4dd1e7b05fc3/fmed-11-1423813-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dd4/11682886/e228998eaab3/fmed-11-1423813-g002.jpg

相似文献

[1]
Artificial intelligence and glaucoma: a lucid and comprehensive review.

Front Med (Lausanne). 2024-12-16

[2]
Promising Artificial Intelligence-Machine Learning-Deep Learning Algorithms in Ophthalmology.

Asia Pac J Ophthalmol (Phila). 2019-5-31

[3]
[Application of artificial intelligence in glaucoma. Part 2. Neural networks and machine learning in the monitoring and treatment of glaucoma].

Vestn Oftalmol. 2024

[4]
Applications of Artificial Intelligence and Deep Learning in Glaucoma.

Asia Pac J Ophthalmol (Phila). 2023

[5]
Artificial intelligence and complex statistical modeling in glaucoma diagnosis and management.

Curr Opin Ophthalmol. 2021-3-1

[6]
Artificial intelligence in the diagnosis of glaucoma and neurodegenerative diseases.

Clin Exp Optom. 2024-3

[7]
Artificial Intelligence Algorithms to Diagnose Glaucoma and Detect Glaucoma Progression: Translation to Clinical Practice.

Transl Vis Sci Technol. 2020-10-15

[8]
Artificial intelligence and deep learning in glaucoma: Current state and future prospects.

Prog Brain Res. 2020

[9]
Artificial intelligence in ophthalmology.

Rom J Ophthalmol. 2023

[10]
[Artificial intelligence and glaucoma: A literature review].

J Fr Ophtalmol. 2022-2

本文引用的文献

[1]
Gemini AI vs. ChatGPT: A comprehensive examination alongside ophthalmology residents in medical knowledge.

Graefes Arch Clin Exp Ophthalmol. 2025-2

[2]
The AI revolution in glaucoma: Bridging challenges with opportunities.

Prog Retin Eye Res. 2024-11

[3]
Predicting Glaucoma Before Onset Using a Large Language Model Chatbot.

Am J Ophthalmol. 2024-10

[4]
Using Large Language Models to Generate Educational Materials on Childhood Glaucoma.

Am J Ophthalmol. 2024-9

[5]
Breaking Barriers in Behavioral Change: The Potential of Artificial Intelligence-Driven Motivational Interviewing.

J Glaucoma. 2024-7-1

[6]
Large language models as assistance for glaucoma surgical cases: a ChatGPT vs. Google Gemini comparison.

Graefes Arch Clin Exp Ophthalmol. 2024-9

[7]
Advancements in Glaucoma Diagnosis: The Role of AI in Medical Imaging.

Diagnostics (Basel). 2024-3-1

[8]
Assessment of a Large Language Model's Responses to Questions and Cases About Glaucoma and Retina Management.

JAMA Ophthalmol. 2024-4-1

[9]
Identifying the Edges of the Optic Cup and the Optic Disc in Glaucoma Patients by Segmentation.

Sensors (Basel). 2023-5-11

[10]
Predicting near-term glaucoma progression: An artificial intelligence approach using clinical free-text notes and data from electronic health records.

Front Med (Lausanne). 2023-4-13

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