Self-supervised learning with electrocardiogram delineation for arrhythmia detection BT Lee, ST Kong, Y Song, Y Lee 2021 43rd Annual International Conference of the IEEE Engineering in …, 2021 | 10 | 2021 |
Aggregation of cohorts for histopathological diagnosis with deep morphological analysis J Park, YR Chung, ST Kong, YW Kim, H Park, K Kim, DI Kim, KH Jung Scientific reports 11 (1), 2876, 2021 | 10 | 2021 |
Manifold ordinal-mixup for ordered classes in TW3-based bone age assessment B Bae, J Lee, ST Kong, J Sung, KH Jung Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 8 | 2020 |
An interpretable and interactive deep learning algorithm for a clinically applicable retinal fundus diagnosis system by modelling finding-disease relationship J Son, JY Shin, ST Kong, J Park, G Kwon, HD Kim, KH Park, KH Jung, ... Scientific Reports 13 (1), 5934, 2023 | 7 | 2023 |
Leveraging the generalization ability of deep convolutional neural networks for improving classifiers for color fundus photographs J Son, J Kim, ST Kong, KH Jung Applied Sciences 11 (2), 591, 2021 | 6 | 2021 |
A Neural Pre-Conditioning Active Learning Algorithm to Reduce Label Complexity ST Kong, S Jeon, D Na, J Lee, HS Lee, KH Jung Advances in Neural Information Processing Systems, 2022 | 5* | 2022 |
Utilizing synthetic nodules for improving nodule detection in chest radiographs M Chung, ST Kong, B Park, Y Chung, KH Jung, JB Seo Journal of Digital Imaging 35 (4), 1061-1068, 2022 | 4 | 2022 |
Almost boltzmann exploration H Gupta, ST Kong, R Srikant, W Wang arXiv preprint arXiv:1901.08708, 2019 | 2 | 2019 |
Key Feature Replacement of In-Distribution Samples for Out-of-Distribution Detection J Kim, ST Kong, D Na, KH Jung Association for the Advancement of Artificial Intelligence, 2023 | 1 | 2023 |
Self-accumulative Vision Transformer for Bone Age Assessment Using the Sauvegrain Method HJ Choi, D Na, K Cho, B Bae, ST Kong, H An arXiv preprint arXiv:2303.16557, 2023 | | 2023 |
A Provably Improved Algorithm for Crowdsourcing with Hard and Easy Tasks ST Kong, S Mandal, D Katselis, R Srikant arXiv preprint arXiv:2302.07393, 2023 | | 2023 |
Volume is All You Need: Improving Multi-task Multiple Instance Learning for WMH Segmentation and Severity Estimation D Lee, C Park, ST Kong, KH Jung, H Heo, SJ Kim Machine Learning in Clinical Neuroimaging: 5th International Workshop, MLCN …, 2022 | | 2022 |
Volume is All You Need: Improving Multi-task Multiple Instance Learning for WMH Segmentation and Severity Estimation W Jung, CH Suh, WH Shim, J Kim, D Lee, C Park, ST Kong, KH Jung, ... International Workshop on Machine Learning in Clinical Neuroimaging, 23-31, 2022 | | 2022 |
Augmenting Magnetic Resonance Imaging with Tabular Features for Enhanced and Interpretable Medial Temporal Lobe Atrophy Prediction D Lee, CH Suh, J Kim, W Jung, C Park, KH Jung, ST Kong, WH Shim, ... International Workshop on Machine Learning in Clinical Neuroimaging, 125-134, 2022 | | 2022 |
Abstraction in Pixel-wise Noisy Annotations Can Guide Attention to Improve Prostate Cancer Grade Assessment H Kim, ST Kong, H Lee, K Kim, KH Jung Workshop on Medical Image Learning with Limited and Noisy Data, 23-31, 2022 | | 2022 |
Method for detecting abnormal findings and generating interpretation text of medical image M Chung, B Park, ST Kong, Y Chung US Patent App. 17/471,001, 2022 | | 2022 |
Method to read chest image B Park, M Chung, ST Kong, Y Chung US Patent App. 17/466,697, 2022 | | 2022 |
Better Optimization can Reduce Sample Complexity: Active Semi-Supervised Learning via Convergence Rate Control ST Kong, S Jeon, J Lee, HS Lee, KH Jung | | 2020 |
Multi-armed bandits and applications to large datasets ST Kong University of Illinois at Urbana-Champaign, 2019 | | 2019 |
Structure identification in layered precedence networks ST Kong, D Katselis, CL Beck, R Srikant 2017 IEEE Conference on Control Technology and Applications (CCTA), 1177-1182, 2017 | | 2017 |