| Magnetic resonance-based texture analysis differentiating KRAS mutation status in rectal cancer JE Oh, MJ Kim, J Lee, BY Hur, B Kim, DY Kim, JY Baek, HJ Chang, ... Cancer research and treatment: official journal of Korean Cancer Association …, 2020 | 75 | 2020 |
| Tumor identification in colorectal histology images using a convolutional neural network H Yoon, J Lee, JE Oh, HR Kim, S Lee, HJ Chang, DK Sohn Journal of digital imaging 32, 131-140, 2019 | 59 | 2019 |
| Reducing the model variance of a rectal cancer segmentation network J Lee, JE Oh, MJ Kim, BY Hur, DK Sohn IEEE Access 7, 182725-182733, 2019 | 23 | 2019 |
| Objective Detection of Oral Carcinoma with Multispectral Fluorescence Lifetime Imaging In Vivo BH Malik, J Lee, S Cheng, R Cuenca, JM Jabbour, YSL Cheng, JM Wright, ... Photochemistry and photobiology 92 (5), 694-701, 2016 | 17 | 2016 |
| Learning missing modal electronic health records with unified multi-modal data embedding and modality-aware attention K Lee, S Lee, S Hahn, H Hyun, E Choi, B Ahn, J Lee Machine Learning for Healthcare Conference, 423-442, 2023 | 13 | 2023 |
| Moving from 2d to 3d: volumetric medical image classification for rectal cancer staging J Lee, J Oh, I Shin, Y Kim, DK Sohn, T Kim, IS Kweon International Conference on Medical Image Computing and Computer-Assisted …, 2022 | 5 | 2022 |
| Self-supervised pre-training improves fundus image classification for diabetic retinopathy J Lee, EJ Lee Real-time image processing and deep learning 2022 12102, 193-198, 2022 | 5 | 2022 |
| Self-supervised Predictive Coding with Multimodal Fusion for Patient Deterioration Prediction in Fine-Grained Time Resolution K Lee, J Won, H Hyun, S Hahn, E Choi, J Lee International Workshop on Trustworthy Machine Learning for Healthcare, 41-50, 2023 | 4 | 2023 |
Bilal MalikQT ImagingVerified email at qtimaging.com
