Development and Validation of Data-Level Innovation Data-Balancing Machine Learning Models for Predicting Optimal Implantable Collamer Lens Size and Postoperative Vault-Reference-Cited by-同舟云学术

Development and Validation of Data-Level Innovation Data-Balancing Machine Learning Models for Predicting Optimal Implantable Collamer Lens Size and Postoperative Vault

Published:2023-11-09 Issue:1 Volume:13 Page:267-286
ISSN:2193-8245
Container-title:Ophthalmology and Therapy
language:en
Short-container-title:Ophthalmol Ther

Author:

Zhao Heng,Tang Tao,Lu Yuchang,Li Xuewei,Sun Liyuan,Chen Sitong,Ma Lu,Luo Yan,Wang Kai^ORCID,Zhao Mingwei

Funder

Capital’s Funds for Health Improvement and Research

National Natural Science Foundation of China

the National Key R&D Program of China

Publisher

Springer Science and Business Media LLC

Subject

Ophthalmology

Link

https://link.springer.com/content/pdf/10.1007/s40123-023-00841-7.pdf

Reference45 articles.

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2. Nakamura T, Isogai N, Kojima T, et al. Posterior chamber phakic intraocular lens implantation for the correction of myopia and myopic astigmatism: a retrospective 10-year follow-up study. Am J Ophthalmol. 2019;206:1–10.

3. Igarashi A, Shimizu K, Kamiya K. Eight-year follow-up of posterior chamber phakic intraocular lens implantation for moderate to high myopia. Am J Ophthalmol. 2014;157:532–9.

4. Assaf JF, Reinstein DZ, Zakka C, et al. Deep learning-based estimation of implantable collamer lens vault using optical coherence tomography. Am J Ophthalmol. 2023;253:29–36.

5. Cao X, Wu W, Wang Y, et al. Comparison over time of vault in Chinese eyes receiving implantable contact lenses with or without a central hole. Am J Ophthalmol. 2016;172:111–7.