Comparison of survival predictions for rats with hemorrhagic shocks using an artificial neural network and support vector machine. - Kyung Hwan Jang; Tae Keun Yoo; Joon Yul Choi; Ki Chang Nam; Jae Lim Choi; Min Kyung Kwon; Deok Won Kim (EMBC, 2011)

A survival prediction model of rats in hemorrhagic shock using the random forest classifier. - Joon Yul Choi; Sung Kean Kim; Wan Hyung Lee; Tae Keun Yoo; Deok Won Kim (EMBC, 2012)

EHS subjects do not perceive RF EMF emitted from smart phones better than non-EHS subjects. - Min Kyung Kwon; Sung Kean Kim; Jeong Mo Koo; Joon Yul Choi; Deok Won Kim (EMBC, 2012)

Mortality prediction of rats in acute hemorrhagic shock using machine learning techniques. - Kyung-Ah Kim; Joon Yul Choi; Tae Keun Yoo; Sung Kean Kim; KilSoo Chung; Deok Won Kim (Medical Biol. Eng. Comput., 2013)

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. - Tae Keun Yoo; Joon Yul Choi; Jeong Gi Seo; Ramasubramanian Bhoopalan; Selvaperumal Sundaramoorthy; Deok Won Kim (Medical Biol. Eng. Comput., 2019)

Advances in gradient echo myelin water imaging at 3T and 7T. - Hyeong-Geol Shin; Se-Hong Oh 001; Masaki Fukunaga; Yoonho Nam; Doo-Hee Lee; Woojin Jung; Minju Jo; Sooyeon Ji; Joon Yul Choi; Jongho Lee 003 (NeuroImage, 2019)

Toward automated severe pharyngitis detection with smartphone camera using deep learning networks. - Tae Keun Yoo; Joon Yul Choi; Younil Jang; Ein Oh; Ik Hee Ryu (Comput. Biol. Medicine, 2020)

A generative adversarial network approach to predicting postoperative appearance after orbital decompression surgery for thyroid eye disease. - Tae Keun Yoo; Joon Yul Choi; Hong Kyu Kim (Comput. Biol. Medicine, 2020)

Deep learning can generate traditional retinal fundus photographs using ultra-widefield images via generative adversarial networks. - Tae Keun Yoo; Ik Hee Ryu; Jin Kuk Kim; In Sik Lee; Jung Sub Kim; Hong Kyu Kim; Joon Yul Choi (Comput. Methods Programs Biomed., 2020)

Exploring linearity of deep neural network trained QSM: QSMnet+. - Woojin Jung; Jaeyeon Yoon; Sooyeon Ji; Joon Yul Choi; Jae Myung Kim; Yoonho Nam; Eung-Yeop Kim; Jongho Lee 003 (NeuroImage, 2020)

Adopting low-shot deep learning for the detection of conjunctival melanoma using ocular surface images. - Tae Keun Yoo; Joon Yul Choi; Hong Kyu Kim; Ik Hee Ryu; Jin Kuk Kim (Comput. Methods Programs Biomed., 2021)

Feasibility study to improve deep learning in OCT diagnosis of rare retinal diseases with few-shot classification. - Tae Keun Yoo; Joon Yul Choi; Hong Kyu Kim (Medical Biol. Eng. Comput., 2021)

Deep learning prediction of steep and flat corneal curvature using fundus photography in post-COVID telemedicine era. - Joon Yul Choi; Hyungsu Kim; Jin Kuk Kim; In Sik Lee; Ik Hee Ryu; Jung Soo Kim; Tae Keun Yoo (Medical Biol. Eng. Comput., 2024)

Development of a generative deep learning model to improve epiretinal membrane detection in fundus photography. - Joon Yul Choi; Ik Hee Ryu; Jin Kuk Kim; In Sik Lee; Tae Keun Yoo (BMC Medical Informatics Decis. Mak., 2024)

Multimodal large language models as assistance for evaluation of thyroid-associated ophthalmopathy. - Bo Ram Kim; Joon Yul Choi; Tae Keun Yoo (Comput. Biol. Medicine, 2025)

Application of multimodal large language models for safety indicator calculation and contraindication prediction in laser vision correction. - Joon Yul Choi; Doo Eun Kim; Sung Jin Kim; Hannuy Choi; Tae Keun Yoo (npj Digit. Medicine, 2025)

Development of a novel scoring system for glaucoma risk based on demographic and laboratory factors using ChatGPT-4. - Joon Yul Choi; Tae Keun Yoo (Medical Biol. Eng. Comput., 2025)