| Deep learning in medical imaging M Kim, J Yun, Y Cho, K Shin, R Jang, H Bae, N Kim Neurospine 16 (4), 657, 2019 | 281 | 2019 |
| Convolutional neural network technology in endoscopic imaging: artificial intelligence for endoscopy J Choi, K Shin, J Jung, HJ Bae, DH Kim, JS Byeon, N Kim Clinical endoscopy 53 (2), 117, 2020 | 56 | 2020 |
| Fully automated 3D segmentation and separation of multiple cervical vertebrae in CT images using a 2D convolutional neural network HJ Bae, H Hyun, Y Byeon, K Shin, Y Cho, YJ Song, S Yi, SU Kuh, ... Computer methods and programs in biomedicine 184, 105119, 2020 | 42 | 2020 |
| Deep learning in medical imaging M Kim, J Yun, Y Cho, K Shin, R Jang, H Bae, N Kim Neurospine 17 (2), 471, 2020 | 20 | 2020 |
| Deep learning–based detection of solid and cystic pancreatic neoplasms at contrast-enhanced CT HJ Park, K Shin, MW You, SG Kyung, SY Kim, SH Park, JH Byun, N Kim, ... Radiology 306 (1), 140-149, 2022 | 18 | 2022 |
| Improved performance and robustness of multi-task representation learning with consistency loss between pretexts for intracranial hemorrhage identification in head CT S Kyung, K Shin, H Jeong, KD Kim, J Park, K Cho, JH Lee, GS Hong, ... Medical Image Analysis 81, 102489, 2022 | 15 | 2022 |
| Overcoming the challenges in the development and implementation of artificial intelligence in radiology: a comprehensive review of solutions beyond supervised learning GS Hong, M Jang, S Kyung, K Cho, J Jeong, GY Lee, K Shin, KD Kim, ... Korean Journal of Radiology 24 (11), 1061, 2023 | 9 | 2023 |
| Can deep learning reduce the time and effort required for manual segmentation in 3D reconstruction of MRI in rotator cuff tears? H Kim, K Shin, H Kim, E Lee, SW Chung, KH Koh, N Kim Plos one 17 (10), e0274075, 2022 | 7 | 2022 |
| Enhancement of evaluating flatfoot on a weight-bearing lateral radiograph of the foot with U-Net based semantic segmentation on the long axis of tarsal and metatarsal bones in … SM Ryu, K Shin, SW Shin, S Lee, N Kim Computers in Biology and Medicine 145, 105400, 2022 | 7 | 2022 |
| Screening of adolescent idiopathic scoliosis using generative adversarial network (GAN) inversion method in chest radiographs JS Lee, K Shin, SM Ryu, SG Jegal, W Lee, MA Yoon, GS Hong, S Paik, ... Plos one 18 (5), e0285489, 2023 | 5 | 2023 |
| Automated landmark identification for diagnosis of the deformity using a cascade convolutional neural network (FlatNet) on weight-bearing lateral radiographs of the foot SM Ryu, K Shin, SW Shin, SH Lee, SM Seo, S Cheon, SA Ryu, JS Kim, ... Computers in Biology and Medicine 148, 105914, 2022 | 5 | 2022 |
| A Study of Cage Rotational Stability of Cryogenic Turbopump Ball Bearing considering on Axial Cooling Flow K Shin Hanyang university, master’s thesis, 2013 | 4 | 2013 |
| An Image Turing Test on Realistic Gastroscopy Images Generated by Using the Progressive Growing of Generative Adversarial Networks K Shin, JS Lee, JY Lee, H Lee, J Kim, JS Byeon, HY Jung, DH Kim, N Kim Journal of Digital Imaging 36 (4), 1760-1769, 2023 | 3 | 2023 |
| Diagnosis of scoliosis using chest radiographs with a semi-supervised generative adversarial network W Lee, K Shin, J Lee, SJ Yoo, MA Yoon, YW Choi, GS Hong, N Kim, ... Journal of the Korean Society of Radiology 83 (6), 1298, 2022 | 3 | 2022 |
| Enhancing the performance of premature ventricular contraction detection in unseen datasets through deep learning with denoise and contrast attention module K Shin, H Kim, WY Seo, HS Kim, JM Shin, DK Kim, YS Park, SH Kim, ... Computers in Biology and Medicine 166, 107532, 2023 | 2 | 2023 |
| Diagnosis of osteoporotic vertebral compression fractures and fracture level detection using multitask learning with U-Net in lumbar spine lateral radiographs SM Ryu, S Lee, M Jang, JM Koh, SJ Bae, SG Jegal, K Shin, N Kim Computational and Structural Biotechnology Journal 21, 3452-3458, 2023 | 2 | 2023 |
| Ryoungwoo Jang Hyun-Jin Bae and Namkug Kim. Deep learning in medical imaging M Kim, J Yun, Y Cho, K Shin Neurospine 16 (4), 657-668, 2019 | 2 | 2019 |
| Machine learning models with time-series clinical features to predict radiographic progression in patients with ankylosing spondylitis BS Koo, M Jang, JS Oh, K Shin, S Lee, KB Joo, N Kim, TH Kim Available at SSRN 4172614, 2021 | 1 | 2021 |
| Integrated clinical and genomic models using machine-learning methods to predict the efficacy of paclitaxel-based chemotherapy in patients with advanced gastric cancer Y Choi, J Lee, K Shin, JW Lee, JW Kim, S Lee, YJ Choi, KH Park, JH Kim BMC cancer 24 (1), 1-9, 2024 | | 2024 |
| METHOD AND APPARATUS FOR ANALYZING BLOOD VESSEL BASED ON MACHINE LEARNING MODEL N Kim, K Shin, D Kim US Patent App. 18/209,389, 2024 | | 2024 |
Namkug Kim, PhDConvergence Medicine, Asan Medical Center, Univ. of Ulsan College of MedicineVerified email at amc.seoul.kr
