Code-Free Machine Learning Approach for EVO-ICL Vault Prediction: A Retrospective Two-Center Study-Reference-Cited by-同舟云学术

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Code-Free Machine Learning Approach for EVO-ICL Vault Prediction: A Retrospective Two-Center Study

Published:2024-04-02 Issue:4 Volume:13 Page:4
ISSN:2164-2591
Container-title:Translational Vision Science & Technology
language:en
Short-container-title:Trans. Vis. Sci. Tech.

Author:

Shin Daeun¹,Choi Hannuy²,Kim Dongyoung³,Park Jaekyung³,Yoo Tae Keun²³,Koh Kyungmin¹

Affiliation:

1. Department of Ophthalmology, Kim's Eye Hospital, Konyang University College of Medicine, Seoul, South Korea

2. Department of Refractive Surgery, B&VIIT Eye Center, Seoul, South Korea

3. Research and Development Department, VISUWORKS, Seoul, South Korea

Publisher

Association for Research in Vision and Ophthalmology (ARVO)

Reference30 articles.

1. Global prevalence of myopia and high myopia and temporal trends from 2000 through 2050;Holden;Ophthalmology,2016

2. Development of a web-based ensemble machine learning application to select the optimal size of posterior chamber phakic intraocular lens;Kang;Transl Vis Sci Technol,2021

3. Comparison of implantation of posterior chamber phakic IOL implantation and laser vision correction in terms of corneal endothelial cells: 3-year observational paired-eye study;Choi;J Cataract Refract Surg,2023

4. Predicting postoperative anterior chamber angle for phakic intraocular lens implantation using preoperative anterior segment metrics;Choi;Transl Vis Sci Technol,2023

5. Prediction of implantable collamer lens vault based on preoperative biometric factors and lens parameters;Di;J Refract Surg,2023

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