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Artificial Intelligence in Ophthalmic Surgery: Current Applications and Expectations.

作者信息

Nuliqiman Maimaiti, Xu Mingyu, Sun Yiming, Cao Jing, Chen Pengjie, Gao Qi, Xu Peifang, Ye Juan

机构信息

Eye Center, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Zhejiang Provincial Key Laboratory of Ophthalmology, Zhejiang Provincial Clinical Research Center for Eye Diseases, Zhejiang Provincial Engineering Institute on Eye Diseases, Hangzhou, Zhejiang, People's Republic of China.

出版信息

Clin Ophthalmol. 2023 Nov 20;17:3499-3511. doi: 10.2147/OPTH.S438127. eCollection 2023.


DOI:10.2147/OPTH.S438127
PMID:38026589
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10674717/
Abstract

Artificial Intelligence (AI) has found rapidly growing applications in ophthalmology, achieving robust recognition and classification in most kind of ocular diseases. Ophthalmic surgery is one of the most delicate microsurgery, requiring high fineness and stability of surgeons. The massive demand of the AI assist ophthalmic surgery will constitute an important factor in boosting accelerate precision medicine. In clinical practice, it is instrumental to update and review the considerable evidence of the current AI technologies utilized in the investigation of ophthalmic surgery involved in both the progression and innovation of precision medicine. Bibliographic databases including PubMed and Google Scholar were searched using keywords such as "ophthalmic surgery", "surgical selection", "candidate screening", and "robot-assisted surgery" to find articles about AI technology published from 2018 to 2023. In addition to the Editorials and letters to the editor, all types of approaches are considered. In this paper, we will provide an up-to-date review of artificial intelligence in eye surgery, with a specific focus on its application to candidate screening, surgery selection, postoperative prediction, and real-time intraoperative guidance.

摘要

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Artificial Intelligence in Ophthalmic Surgery: Current Applications and Expectations.

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[3]
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[4]
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[5]
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本文引用的文献

[1]
Trocar localisation for robot-assisted vitreoretinal surgery.

Int J Comput Assist Radiol Surg. 2024-2

[2]
Deep learning-based image analysis of eyelid morphology in thyroid-associated ophthalmopathy.

Quant Imaging Med Surg. 2023-3-1

[3]
Harnessing Generative Artificial Intelligence to Improve Efficiency Among Urologists: Welcome ChatGPT.

J Urol. 2023-5

[4]
An overview of artificial intelligence in diabetic retinopathy and other ocular diseases.

Front Public Health. 2022

[5]
Evolution and Applications of Artificial Intelligence to Cataract Surgery.

Ophthalmol Sci. 2022-4-25

[6]
Accuracy of Six Intraocular Lens Power Calculations in Eyes with Axial Lengths Greater than 28.0 mm.

J Clin Med. 2022-10-8

[7]
Optical Coherence Tomography-Guided Robotic Ophthalmic Microsurgery via Reinforcement Learning from Demonstration.

IEEE Trans Robot. 2020-8

[8]
Effect of Multichannel Convolutional Neural Network-Based Model on the Repair and Aesthetic Effect of Eye Plastic Surgery Patients.

Comput Math Methods Med. 2022

[9]
A Novel Microsurgical Robot: Preliminary Feasibility Test in Ophthalmic Field.

Transl Vis Sci Technol. 2022-8-1

[10]
Intelligent cataract surgery supervision and evaluation via deep learning.

Int J Surg. 2022-8

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