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Ik Hee Ryu

Showing results (1-10 of 45) with videos related to

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Japanese Journal of Ophthalmology|June 22, 2016
Age-related differences in corneal epithelial thickness measurements with anterior segment optical coherence tomographyBong Jun Kim, Ik-Hee Ryu, Sun Woong Kim
Journal of Clinical Medicine|December 2, 2020
Effect of Gender, Age, and Ocular and Growth-Related Factors on Corneal Epithelial and Stromal Thickness in ChildrenWook Kyum Kim, Ik Hee Ryu, Jeongseo Yoo, et al.
Annals of Translational Medicine|October 21, 2022
The role of big data analysis in identifying a relationship between glaucoma and diabetes mellitusEin Oh, Yong Hyun Kim, Ik Hee Ryu, et al.
Eye and Vision (London, England)|February 3, 2022
Application of generative adversarial networks (GAN) for ophthalmology image domains: a surveyAram You, Jin Kuk Kim, Ik Hee Ryu, et al.
Eye (London, England)|October 6, 2021
Deep learning for predicting uncorrected refractive error using posterior segment optical coherence tomography imagesTae Keun Yoo, Ik Hee Ryu, Jin Kuk Kim, et al.
Journal of Refractive Surgery (Thorofare, N.J. : 1995)|April 14, 2017
Comparison of Corneal Epithelial Remodeling After Femtosecond Laser-Assisted LASIK and Small Incision Lenticule Extraction (SMILE)Ik-Hee Ryu, Bong Jun Kim, Jong-Hyuck Lee, et al.
Cornea|May 27, 2016
Correlation of Sex and Myopia With Corneal Epithelial and Stromal ThicknessesBong Jun Kim, Ik-Hee Ryu, Jong-Hyuck Lee, et al.
Computers in Biology and Medicine|September 2, 2020
Toward automated severe pharyngitis detection with smartphone camera using deep learning networksTae Keun Yoo, Joon Yul Choi, Younil Jang, et al.
European Journal of Ophthalmology|April 2, 2026
Vertical-horizontal rotation of EVO-ICL to correct suboptimal vault based on vertically oval sulcus anatomyHannuy Choi, Ik Hee Ryu, In Sik Lee, et al.
BMC Medical Informatics and Decision Making|March 7, 2025
Retinal vein occlusion risk prediction without fundus examination using a no-code machine learning tool for tabular data: a nationwide cross-sectional study from South KoreaNa Hyeon Yu, Daeun Shin, Ik Hee Ryu, et al.
Pageof 5

Showing results (1-10 of 45) with videos related to

Sort By:
Pageof 5
Japanese Journal of Ophthalmology|June 22, 2016
Age-related differences in corneal epithelial thickness measurements with anterior segment optical coherence tomographyBong Jun Kim, Ik-Hee Ryu, Sun Woong Kim
Journal of Clinical Medicine|December 2, 2020
Effect of Gender, Age, and Ocular and Growth-Related Factors on Corneal Epithelial and Stromal Thickness in ChildrenWook Kyum Kim, Ik Hee Ryu, Jeongseo Yoo, et al.
Annals of Translational Medicine|October 21, 2022
The role of big data analysis in identifying a relationship between glaucoma and diabetes mellitusEin Oh, Yong Hyun Kim, Ik Hee Ryu, et al.
Eye and Vision (London, England)|February 3, 2022
Application of generative adversarial networks (GAN) for ophthalmology image domains: a surveyAram You, Jin Kuk Kim, Ik Hee Ryu, et al.
Eye (London, England)|October 6, 2021
Deep learning for predicting uncorrected refractive error using posterior segment optical coherence tomography imagesTae Keun Yoo, Ik Hee Ryu, Jin Kuk Kim, et al.
Journal of Refractive Surgery (Thorofare, N.J. : 1995)|April 14, 2017
Comparison of Corneal Epithelial Remodeling After Femtosecond Laser-Assisted LASIK and Small Incision Lenticule Extraction (SMILE)Ik-Hee Ryu, Bong Jun Kim, Jong-Hyuck Lee, et al.
Cornea|May 27, 2016
Correlation of Sex and Myopia With Corneal Epithelial and Stromal ThicknessesBong Jun Kim, Ik-Hee Ryu, Jong-Hyuck Lee, et al.
Computers in Biology and Medicine|September 2, 2020
Toward automated severe pharyngitis detection with smartphone camera using deep learning networksTae Keun Yoo, Joon Yul Choi, Younil Jang, et al.
European Journal of Ophthalmology|April 2, 2026
Vertical-horizontal rotation of EVO-ICL to correct suboptimal vault based on vertically oval sulcus anatomyHannuy Choi, Ik Hee Ryu, In Sik Lee, et al.
BMC Medical Informatics and Decision Making|March 7, 2025
Retinal vein occlusion risk prediction without fundus examination using a no-code machine learning tool for tabular data: a nationwide cross-sectional study from South KoreaNa Hyeon Yu, Daeun Shin, Ik Hee Ryu, et al.
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