Joon Yul Choi
According to our database1,
Joon Yul Choi
authored at least 14 papers
between 2011 and 2024.
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Bibliography
2024
Development of a generative deep learning model to improve epiretinal membrane detection in fundus photography.
BMC Medical Informatics Decis. Mak., December, 2024
Deep learning prediction of steep and flat corneal curvature using fundus photography in post-COVID telemedicine era.
Medical Biol. Eng. Comput., February, 2024
2021
Feasibility study to improve deep learning in OCT diagnosis of rare retinal diseases with few-shot classification.
Medical Biol. Eng. Comput., 2021
Adopting low-shot deep learning for the detection of conjunctival melanoma using ocular surface images.
Comput. Methods Programs Biomed., 2021
2020
NeuroImage, 2020
Deep learning can generate traditional retinal fundus photographs using ultra-widefield images via generative adversarial networks.
Comput. Methods Programs Biomed., 2020
A generative adversarial network approach to predicting postoperative appearance after orbital decompression surgery for thyroid eye disease.
Comput. Biol. Medicine, 2020
Toward automated severe pharyngitis detection with smartphone camera using deep learning networks.
Comput. Biol. Medicine, 2020
2019
The possibility of the combination of OCT and fundus images for improving the diagnostic accuracy of deep learning for age-related macular degeneration: a preliminary experiment.
Medical Biol. Eng. Comput., 2019
2013
Mortality prediction of rats in acute hemorrhagic shock using machine learning techniques.
Medical Biol. Eng. Comput., 2013
2012
EHS subjects do not perceive RF EMF emitted from smart phones better than non-EHS subjects.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012
A survival prediction model of rats in hemorrhagic shock using the random forest classifier.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012
2011
Comparison of survival predictions for rats with hemorrhagic shocks using an artificial neural network and support vector machine.
Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011