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Jin Kuk Kim
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2020 – today
- 2024
- [j6]Joon Yul Choi, Hyungsu Kim, Jin Kuk Kim, In Sik Lee, Ik Hee Ryu, Jung Soo Kim, Tae Keun Yoo:
Deep learning prediction of steep and flat corneal curvature using fundus photography in post-COVID telemedicine era. Medical Biol. Eng. Comput. 62(2): 449-463 (2024) - [j5]Joon Yul Choi, Ik Hee Ryu, Jin Kuk Kim, In Sik Lee, Tae Keun Yoo:
Development of a generative deep learning model to improve epiretinal membrane detection in fundus photography. BMC Medical Informatics Decis. Mak. 24(1): 25 (2024) - 2022
- [j4]Tae Keun Yoo, Ik Hee Ryu, Jin Kuk Kim, In Sik Lee, Hong Kyu Kim:
A deep learning approach for detection of shallow anterior chamber depth based on the hidden features of fundus photographs. Comput. Methods Programs Biomed. 219: 106735 (2022) - 2021
- [j3]Tae Keun Yoo, Joon Yul Choi, Hong Kyu Kim, Ik Hee Ryu, Jin Kuk Kim:
Adopting low-shot deep learning for the detection of conjunctival melanoma using ocular surface images. Comput. Methods Programs Biomed. 205: 106086 (2021) - 2020
- [j2]Tae Keun Yoo, Ik Hee Ryu, Jin Kuk Kim, In Sik Lee, Jung Sub Kim, Hong Kyu Kim, Joon Yul Choi:
Deep learning can generate traditional retinal fundus photographs using ultra-widefield images via generative adversarial networks. Comput. Methods Programs Biomed. 197: 105761 (2020)
2010 – 2019
- 2019
- [j1]Tae Keun Yoo, Ik Hee Ryu, Geunyoung Lee, Youngnam Kim, Jin Kuk Kim, In Sik Lee, Jung Sub Kim, Tyler Hyungtaek Rim:
Adopting machine learning to automatically identify candidate patients for corneal refractive surgery. npj Digit. Medicine 2 (2019)
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last updated on 2024-04-24 23:09 CEST by the dblp team
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