Prediction of visual field progression in glaucoma: existing methods and artificial intelligence-Reference-Cited by-同舟云学术

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Prediction of visual field progression in glaucoma: existing methods and artificial intelligence

Published:2023-08-04 Issue:5 Volume:67 Page:546-559
ISSN:0021-5155
Container-title:Japanese Journal of Ophthalmology
language:en
Short-container-title:Jpn J Ophthalmol

Author:

Asaoka Ryo,Murata Hiroshi

Funder

ministry of education, culture, sports, science, and technology of Japan

ministry of education, culture, sports, science and technology of Japan

japan agency for medical reserach and development

the Japan Glaucoma Society Project Support Program

Publisher

Springer Science and Business Media LLC

Subject

Ophthalmology,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s10384-023-01009-3.pdf

Reference108 articles.

1. Scerri M, Grech V. Artificial intelligence in medicine. Early Hum Dev. 2020;145:105017.

2. Jampel HD. Target pressure in glaucoma therapy. J Glaucoma. 1997;6:133–8.

3. Clement CI, Bhartiya S, Shaarawy T. New perspectives on target intraocular pressure. Surv Ophthalmol. 2014;59:615–26.

4. The Japan Glaucoma Society. The Japan Glaucoma Society Guidelines for Glaucoma (5th edition). Nippon Ganka Gakkai Zasshi. 2022;126:85–177.

5. Kiuchi Y, Inoue T, Shoji N, Nakamura M, Tanito M. Glaucoma Guideline Preparation Committee, Japan Glaucoma Society. The Japan Glaucoma Society Guidelines for glaucoma. Jpn J Ophthalmol. 2023;67:189–254.

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