Reducing the Model Variance of a Rectal Cancer Segmentation Network. - Joohyung Lee 003; Ji Eun Oh; Min Ju Kim; Bo Yun Hur; Dae Kyung Sohn (IEEE Access, 2019)

Multi-Task Learning with a Fully Convolutional Network for Rectum and Rectal Cancer Segmentation. - Joohyung Lee 003; Ji Eun Oh; Min Ju Kim; Bo Yun Hur; Sun Ah Cho; Dae Kyung Sohn (CoRR, 2019)

Rectal cancer: Toward fully automatic discrimination of T2 and T3 rectal cancers using deep convolutional neural network. - Jongin Kim; Ji Eun Oh; Joohyung Lee 003; Min Ju Kim; Bo Yun Hur; Dae Kyung Sohn; Boreom Lee (Int. J. Imaging Syst. Technol., 2019)

Tumor Identification in Colorectal Histology Images Using a Convolutional Neural Network. - Hongjun Yoon; Joohyung Lee 003; Ji Eun Oh; Hong Rae Kim; Seonhye Lee; Hee Jin Chang; Dae Kyung Sohn (J. Digit. Imaging, 2019)

Moving from 2D to 3D: Volumetric Medical Image Classification for Rectal Cancer Staging. - Joohyung Lee 003; Jieun Oh; Inkyu Shin; You-sung Kim; Dae Kyung Sohn; Tae-sung Kim; In So Kweon (MICCAI (3), 2022)

Self-supervised predictive coding and multimodal fusion advance patient deterioration prediction in fine-grained time resolution. - Kwanhyung Lee; John Won; Heejung Hyun; Sangchul Hahn; Edward Choi; Joohyung Lee 003 (CoRR, 2022)

Learning Missing Modal Electronic Health Records with Unified Multi-modal Data Embedding and Modality-Aware Attention. - Kwanhyung Lee; Soojeong Lee; Sangchul Hahn; Heejung Hyun; Edward Choi; Byungeun Ahn; Joohyung Lee 003 (MLHC, 2023)

Self-supervised Predictive Coding with Multimodal Fusion for Patient Deterioration Prediction in Fine-Grained Time Resolution. - Kwanhyung Lee; John Won; Heejung Hyun; Sangchul Hahn; Edward Choi; Joohyung Lee 003 (TML4H, 2023)

Compact and De-Biased Negative Instance Embedding for Multi-Instance Learning on Whole-Slide Image Classification. - Joohyung Lee 003; Heejeong Nam; Kwanhyung Lee; Sangchul Hahn (ICASSP, 2024)