| Radiomics-guided deep neural networks stratify lung adenocarcinoma prognosis from CT scans H Cho, HY Lee, E Kim, G Lee, J Kim, J Kwon, H Park Communications biology 4 (1), 1286, 2021 | 25 | 2021 |
| Radiomics based on thyroid ultrasound can predict distant metastasis of follicular thyroid carcinoma M Kwon, JH Shin, H Park, H Cho, E Kim, SY Hahn Journal of clinical medicine 9 (7), 2156, 2020 | 22 | 2020 |
| Tumor-attentive segmentation-guided GAN for synthesizing breast contrast-enhanced MRI without contrast agents E Kim, HH Cho, J Kwon, YT Oh, ES Ko, H Park IEEE journal of translational engineering in health and medicine 11, 32-43, 2022 | 15 | 2022 |
| Novel multiparametric magnetic resonance imaging-based deep learning and clinical parameter integration for the prediction of long-term biochemical recurrence-free survival in … HW Lee, E Kim, I Na, CK Kim, SI Seo, H Park Cancers 15 (13), 3416, 2023 | 7 | 2023 |
| Generative adversarial network with local discriminator for synthesizing breast contrast-enhanced MRI E Kim, H Cho, E Ko, H Park 2021 IEEE EMBS International Conference on Biomedical and Health Informatics …, 2021 | 6 | 2021 |
| Deep learning analysis to predict EGFR mutation status in lung adenocarcinoma manifesting as pure ground-glass opacity nodules on CT HJ Yoon, J Choi, E Kim, SW Um, N Kang, W Kim, G Kim, H Park, HY Lee Frontiers in Oncology 12, 951575, 2022 | 5 | 2022 |
| Incremental benefits of size-zone matrix-based radiomics features for the prognosis of lung adenocarcinoma: advantage of spatial partitioning on tumor evaluation E Kim, G Lee, S Lee, H Cho, HY Lee, H Park European Radiology 32 (11), 7691-7699, 2022 | 2 | 2022 |
